# Chapter 5 · Writing pages (3): quick cards for 33 more page types

> GEO Playbook · General Edition v1.0 · Canlah AI · CC BY 4.0 · Web page: https://canlah.ai/playbook/page-types-more/
> Markdown edition for AI assistants, same content as the web page. Figures are code blocks (wireframe / mermaid / bars / steps / split); "→" links open the matching section on the web, and the same URL with .md is its Markdown edition.

## 5.21 Tier-B price types: subsidy limits, parameter basis, category lists, calculators, time-limited promotions

**What you'll do in this section**: give each of these question shapes its own page: "how much do I pay after the subsidy" / "how much would I pay in my situation" / "which brands are there and what price range" / "how is it calculated". When you're done, you'll have five blueprints, each with the numbers AI cannot work out for itself (the price you actually charge, the unit price, the effective period, whether tax is included) fixed in the first screen.

```mermaid Figure: AI skips the calculator, does the maths itself from the unit price and the limit, and only lacks your own number
flowchart LR
  q["Buyer asks how much to pay"] --> ai["ChatGPT"]
  ai -->|skips| tool["Interactive calculator widget"]:::warn
  ai -->|pulls data| src["Unit price, limit, pricing page"]:::hl
  src -->|builds formula| out["Estimate table in the answer"]
  own["The price you actually charge"] -->|gets in only if fixed in first screen| out
```

This pattern recurs across three industries (evidence in Appendix A.4). Each of the five types below supplies one cell of this estimate table; the cards do not repeat this point.

### 5.21.1 Subsidy and limit rules page (pt17)

**Intent**: "How do I apply, how do I claim" and "how much do I pay after the subsidy" share this type. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: H1 = the scheme's full name with its abbreviation; a short summary on the line under H1, with `Last updated <day month year>` in the first screen. This type wins on number density, not on images.

```wireframe id=pt17 Figure: Subsidy and limit rules page; AI copies cells from the itemised limit table
H1 | scheme's full name with abbreviation | req
First-screen summary + update date | one summary sentence, update date in the first screen not the footer | req
H2, three to four questions | What is it / Benefits / Who is eligible / How to use | req
Itemised limit table | one row per item + upper limit amount | req,cite
Old and new tables side by side | when limits change: one current table, one for the new effective date | opt
Eligibility table | which group can use which tier, listed by group | req
Numbered procedure steps | download form → fill in → submit | opt
Your own three-column table | item / limit / what you pay; availability depends on the side | opt,law
```

**Standard column headers**: official table `S/N / <service category> / Claim limits / Current Subsidy amount (Up to $)`; your own version `Item / Limit / What you pay`.
**Sample sentences**: own sentence (holds only on the lightly regulated and unregulated sides) — "<item name>: we charge S$<final tax-inclusive price>; with us, this item's <subsidy scheme> code is <code>, which offsets S$<amount>; you pay S$<amount>." Market sentence — copy the official limit as is, label the table number and update date, and give it its own section.

> **Example** (healthcare subsidies) The sentence giving the limits (up to $830 per day, $240–$5,290 for surgical items; paraphrased) was lifted whole from the official subsidy page; the source is a cell in the itemised limit table. AI then combines it with the fee benchmark and the "can I claim" rule to do the maths on the spot. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: your own three-column table and the "you pay" sentence hold only on the lightly regulated and unregulated sides; on the strictly regulated side your own version may be built after rewriting: the subsidy stays in its own factual section, in a different table from your own price, not adjacent to it, and there is no case-by-case confirmation tier. See the price row and the dedicated price-family row in 5.2 for the wording.

**Most common mistake**: building a subsidy calculator. What you need to give is the number AI cannot calculate: the price you actually charge and your own coding result.

### 5.21.2 Parameter and rate basis page (pt27)

**Intent**: "how much would I pay in my situation", "X calculator", "how much a month". It is used as a calculation input, not for comparing prices — that is what sets it apart from （→ 通用版 5.14 官方定价页（pt03））. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: both forms get cited — the original-question form (`What is the <parameter name>?`, one question one answer), or the category + location form (H1 without a year, without "calculator").

```wireframe id=pt27 Figure: Parameter and rate basis page; AI copies the current value given as a tax-exclusive and tax-inclusive pair
title | the original-question form, or the category + location form | req
First-screen basis sentence | who sets the price, how often it is adjusted | req
Current value as a pair | tax-exclusive and tax-inclusive values fixed in the same sentence | req,cite
Time-tiered table | parameter name / current value / effective period | req
Single current-value sentence | one sentence stating the current figure and the year it took effect | req,cite
Formula and worked example | total formula + a three-column worked example (not measured) | opt
Units H2 | unit and average usage | opt
Everything in static HTML | the numbers are still there with JS off | req
```

**Standard column headers**: `<parameter name> / <annual cap or unit price> / effective period`, one row per tier.
**Sample sentences**: own sentence — "<parameter name> has been <value> (<tax basis>) since <effective date>, adjusted every <period>." Market sentence — write out the formula: "<total> = <parameter A> × <parameter B> × <parameter C>".

> **Example** (payroll contributions) Two things were lifted from the official wage-ceiling page: the sentence "It was gradually raised and has reached $8,000 in 2026." and the last row of the tiered table. What AI wants is an authoritative source for each parameter in the formula. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: none. For how to turn a parameter into a final tax-inclusive price, see the dedicated price-family row in 5.2.

**Most common mistake**: spending effort on an interactive calculator page. The value, the basis and the effective date are all required — fix all three in static HTML in the first screen.

### 5.21.3 Category list page (pt37)

**Intent**: the "which brands are there, what's the price range" part of a full-guide question. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: title = `Shop <synonym A> & <synonym B> for <audience>` + site name. H1 can be a selling-point sentence; it is not the part that gets cited, so don't spend effort on it.

```wireframe id=pt37 Figure: Category list page; AI copies the total product count, the price endpoints and the brand wall
title | category synonyms side by side + audience + site name | req
H1 | a selling-point sentence is enough; not cited | opt
Total product count + price endpoints | N Products; one figure each for lowest and highest price | req,cite
Brand wall | each brand name as its own text item | req,cite
Type filter panel | each type name as its own text item | req
Bottom explanatory section | one or two H2s, not a source of copied sentences | opt
Only inside a JS facet | count, price and brand not rendered as static text | no
```

**Standard column headers**: this type relies on plain text in the filter panel, not a table; if you add one, use `Brand / Price range / Number of models on sale` (not measured).
**Sample sentences**: "<category> on <this site> has <N> models in total, priced from S$<lowest> to S$<highest>, covering <brand 1, brand 2…>." This sentence is also the market sentence — AI takes it as the size and price range of the category, one of the few page types where the two sentences merge into one.

> **Example** (mother-and-baby e-commerce) A stroller category page was copied whole into a market overview sentence: 169 models, about S$112 to S$3,045, nine brands. A comparable page on another site rendered the whole thing in JS, with 0 words of static HTML body text; it was listed as a citation but not one sentence was actually copied. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: on the strictly regulated side and where switch E (peer comparison banned) is on, do not build this (no listing of peers, no side-by-side line-up across the category); build the organisation's own service catalogue instead. On the lightly regulated side it may be built after rewriting, as the organisation's own catalogue. Where switch B (legally required fields) is on, every item's name in the catalogue must match the registered name word for word.

**Most common mistake**: the product count, price endpoints and brand list exist only in the facet's JS. If they don't render as static text, being cited counts for nothing.

### 5.21.4 Calculator page (pt38)

**Intent**: "How do I calculate my X", "which tier does <score> fall into", "X calculator". **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: title = H1 = `<tool name> <year> — <what it calculates>` + site name.

```wireframe id=pt38 Figure: Calculator page; what gets copied is the first-screen tier conclusion and the static reference table, not the widget
title = H1 | tool name + year + what it calculates + site name | req
First-screen tier conclusion | one sentence with a number range: tier A maps to X, tier B maps to Y | req,cite,law
Calculator widget | JS, cited 0 times, don't invest in it | opt
Large static reference table | pre-computes and lays out the results flat | req,cite
FAQ | 5 questions, restating the definition of the calculation | opt
Definition sentence for the calculation | one sentence: how it's added up, what the range is | req
```

**Standard column headers**: `<input tier> / <result> / <conditions it suits>` (cross-industry analogy, not measured).
**Sample sentences**: own sentence — "<input> under <basis> maps to <result>; <result range A> applies to <scenario A>, <result range B> applies to <scenario B>." It must carry a number range; never write "it varies from person to person". Market sentence — write the public distribution under that basis as one sentence, labelled with the data date.

> **Example** (school admissions) Three things were copied from a score-calculator page: the first-screen tier conclusion, the body rows of the reference table, and the sentence defining the calculation (4 subjects added up, range 4–32); the calculator widget itself was not copied. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: on the strictly regulated side the calculator's output must never be a price commitment — it may only estimate process (number of visits, duration); the static table should only carry fixed-price items. Where switch E (peer comparison banned) is on, write "subject to formal engagement", and do not compare prices with peers.

**Most common mistake**: building a beautiful JS calculator and nothing else on the page. Handover test: turn off JS — the page should still have a tier conclusion sentence and a static table left.

### 5.21.5 Time-limited promotion page (pt42)

**Intent**: when AI answers "how is this business", it goes looking for the business's actual current price. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: the page body itself could not be retrieved and can only be worked out backwards from the URL, so we give no formula for title and H1.

```wireframe id=pt42 Figure: Time-limited promotion page; only three things were verified, nothing else was guessed
One URL per promotion | numbered, each promotion its own page | req
Fixed nett price + scope | one sentence: bundle contents, price, participating outlets | req,law
Listed under a news/updates section | URL path checkable | req
title, H1 and the remaining blocks | page body could not be retrieved, not guessed | opt
```

Use all three as clues, not as conclusions. In the one measured question, this type of page was the only citation from the business itself, with a price, that AI wrote into the answer as a positive fact; the homepage only contributed a neutral fact — the number of branches (evidence in Appendix A.4).

**Standard column headers**: none (layout not retrieved).
**Sample sentences**: own sentence (the shape of the cited sentence) — "<item A + item B + item C> S$<price> nett, valid at <participating outlets>." No market sentence applies.

```split Figure: the cited promotion wording, and how the strictly regulated side replaces it with a standing fixed price in the same spot
The cited promotion wording || The strictly regulated side's replacement wording
One URL per promotion, listed under news/updates || One URL per bundle, standing
<bundle> S$<price> nett, time-limited || S$<final tax-inclusive price>, including <mandatory items>
Valid at participating outlets || State which outlets it applies to
Carries a validity period and promotional wording || Drop the time-limited and promotional wording
```

This kind of page as cited cannot be built as-is on the strictly regulated side — what wins rankings does not decide compliance; the rules and labels for the promotion cell are in the promotion row of 5.2.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: where switch B (legally required fields) is on, write the discount in full: validity period, conditions, currency, whether tax is included, payment method.

**Most common mistake**: cramming every promotion into one "latest offers" list page. With ten promotions listed on one page, AI cannot tell which price maps to which item.
## 5.22 Tier-B selection and reputation types: third-party reviews, sentiment and forums, review aggregates, self-built reputation, verdict-first

**What you'll do in this section**: work out, inside the answer to "is this business good", which page type each of the four blocks — neutral facts, pros, cons, and the scored rating — comes from. When you're done, you'll have five blueprints, and you'll know which ones you can build yourself and which ones you can only nudge into position by supplying facts.

```mermaid Figure: the answer to "is this business good" splits into four blocks; the cons block comes only from pages you don't control
flowchart LR
  q["Is this business good"] --> neutral["Neutral facts"]
  q --> pros["Pros"]
  q --> cons["Cons and reputation disagreement"]:::hl
  q --> score["Score with a denominator"]
  neutral -->|from| site["Own site – can build"]
  pros -->|from| site
  pros -->|from| own["Self-built reputation page – can build"]
  pros -->|from| rpros["Review page Pros"]
  cons -->|from| rcons["Review page Cons – third-party"]:::warn
  cons -->|from| forum["Sentiment, forums, news – cannot build"]:::warn
  score -->|from| agg["Review aggregate – strict or E: cannot build"]:::warn
  score -->|from| own
```

For pt25, marked "cannot build" in the figure, on every side you can only supply checkable facts, make sure you are listed on the platform, and keep the platform information matching your own site. pt28, the review aggregate page, has different availability by side: on the strictly regulated side and where switch E (peer comparison banned) is on, you may not self-build it (a rating is a testimonial, Statute text); on the lightly regulated side it may be built after rewriting (testimonials carry a name, relationship and year); on the unregulated side it may be built. Only the unregulated side can self-build the review page: you can write a review of a competitor and cast yourself as the alternative, to take that seat. The verdict-first page as a whole type is only built on the unregulated side; on the lightly regulated side, after rewriting, only the scenario comparison table (5.22.5) may be built. The self-built reputation page only supplies the positive half, and is not built on the strictly regulated side. For whether each side may write testimonials and how to write a rating, see （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）; not repeated here.

### 5.22.1 Third-party single-business review (pt24)

**Intent**: "is <a business> good", "<a model> review", "is it worth it". In the same question, ChatGPT gets specs and price from the official PDP; subjective pros and cons can only come from this type. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: the media version is a first-person verdict sentence, a long headline, naming competitors and stating reservations; the institutional version is written as "<institution> vs <alternative>". The line under H1 has the byline + publish date — this type has the highest byline rate of any type in the book.

```wireframe id=pt24 Figure: Third-party single-business review; AI copies the fee snapshot and the Cons
Byline + update date | one line, name + publish or update date | req
Fee snapshot table | <tier> / Estimated monthly fee, in the first 25% of the page | req,cite
Pros block | one sentence per item, 4–8 items | req
Cons block | one sentence per item, the negatives the official site would never write | req,cite
Comparison table | Feature / Competitor / Our option | opt
Short conversational H2s | each one carries one citable judgement, no table | opt
Conclusion paragraph | one paragraph: a verdict for the scenarios it suits and those it doesn't | req
```

**Standard column headers**: `<tier> / Estimated monthly fee (<year>)` (fee snapshot table); `Feature / <competitor> / <own>` (comparison table, unregulated side only).
**Sample sentences**: this type is written by a third party, so there is no own sentence; the market sentence is the Cons item itself, shaped like "trigger operation can be annoying — you must hold the trigger down" or "motor-heavy design feels awkward in handheld mode". ChatGPT attributes the Pros to the official site and the Cons to this type.

> **Example** (education and training) The fee snapshot table of a third-party review page (Sec 3–4 S$360–420/month, JC H2 S$400–480/month) and its Pros/Cons wording were copied, from a position in the first 25% of the page. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: not built on either the strictly or lightly regulated side (Conservative line (not statute text)); not built where switch E (peer comparison banned) is on. It may only be self-built on the unregulated side, where you can cast yourself as the alternative in a review of a competitor, capturing the question that names the competitor's brand.

**Most common mistake**: putting the rating and conclusion entirely in JS. With JS off, the body text is nothing but navigation — listed as a citation, but with not one sentence to copy.

### 5.22.2 Sentiment, forum and news pages (pt25)

**Intent**: the negative side of "is this business good". You cannot build this type, but it sets the ceiling for your own site's pages. **Leg**: ChatGPT (AI Mode not measured).
**Carriers**: news page H1 = an event sentence, amounts down to the cent; Reddit post H1 = the original question, with multiple replies; forum thread URL paginated by reply page, H1 = the thread title, each reply has username + timestamp + body text, no rating system.

```wireframe id=pt25 Figure: the three sentiment, forum and news carriers (observed; cannot self-build)
News page H1 | an event sentence: the parties + the organisation + the amount
Reddit post H1 | the original question
Forum thread H1 | the thread title, URL with the reply-page number
Each reply's structure | username + timestamp + body text + reply count
Pagination depth | AI pages deep into reply pages, not just the first page
```

All three carriers are observed (some pages could not be retrieved; read only from the cited sentence) — **you cannot build this type**. For the forum part, AI summarises; it does not copy a single sentence.

> **Example** (dental) Of the 5 citations in an answer to "is this business good", 2 were sentiment sources: a news article was copied into an account of a bill a woman was given after a scaling appointment (the amount down to the cent), and a Reddit post was copied into "some users say [it] was okay; others complain about rushed cleaning, high bills, or upselling." AI added its own line, "treat those as anecdotes, not proof", but still wrote it into the body of the answer. Evidence in Appendix A.4.

**Defence** (the only three things you can do):
1. Lay out checkable facts (price list, nett price, credentials, branch opening hours) so AI finds them on the first search, crowding out its motive to go digging through forums. Brand-review questions are not won by adding more pages.
2. Respond to common complaints directly on your own page, so that when AI restates a complaint it may cite your response. ⚠️ This is inferred, not measured.
3. Recognise that your own site only supplies neutral facts such as branch count — the half-sentence in an answer that calls the reputation mixed has only this one source; neither your own site nor review pages can supply the negative, and the two sentences that set the tone come from pages you don't control.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: on every side this type cannot be self-built; you can only supply facts and make sure you are listed on the platform with information matching your own site. On the strictly regulated side, you may not respond with comparisons or mobilise testimonials to counter it.

**Most common mistake**: paying for brand-polishing content. In the measured case, not one of these made it into the answer; what made it in was checkable numbers and the forum's own words.

### 5.22.3 Review aggregate page (pt28)

**Intent**: "is <an organisation> good", "how's <brand>", "reviews from parents". This type explains where the half of citations you don't control comes from in "who's best" questions — it can be generated programmatically, one URL per branch the organisation has. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: title puts the review count in the title itself (`<organisation (branch)> - N Reviews - <category> - <platform>`). H1 = the organisation name with a branch suffix.

```wireframe id=pt28 Figure: Review aggregate page; AI copies the aggregate value with its denominator, not the review text itself
First-screen rating widget | score + N reviews + category, no preamble | req,cite
Sub-score table | sub-score name + score | opt
Organisation facts block | phone, email, address | req
Opening-hours table | day + time slot + status | req
FAQ restating the score | the score written again under an H3 question | opt
Paginated review feed | item by item: name, date, star rating, body text | opt
schema | AggregateRating + LocalBusiness, matching the first-screen figures | req
```

**Standard column headers**: `Weekday / Schedule / Status` (opening hours).
**Sample sentences**: does not apply on the strictly regulated side or where switch E is on. Market sentence (the shape AI wants) — "<organisation> (<branch>) <rating>/5, <N> reviews", the score plus the sample size; the star rating alone is not used.

> **Example** (dental) The first-screen "4.2/5 with 113 reviews" was copied whole, and copied side by side across three branches within the same answer. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: not self-built on the strictly regulated side or where switch E (peer comparison banned) is on (a rating is a testimonial, Statute text); on the lightly regulated side it may be built after rewriting, with testimonials carrying a name, relationship and year; what can be done is limited to making sure you're listed on local directories and review platforms, that reviews carry dates, that each branch has its own URL, and that the address and phone number on the platform match your own site.

**Most common mistake**: thinking that putting a positive review on your own site offsets this. AI wants a third-party aggregate value with a denominator, which your own testimonial page cannot supply.

### 5.22.4 Self-built reputation and credentials page (pt29)

**Intent**: "is <a business> good". This is the only type you can self-build for review questions. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: the title carries a ranking claim, or is written as "Award Winning <business> | <brand>". Numbers must go into an H2 or a stand-alone sentence, not scattered through a paragraph.

```wireframe id=pt29 Figure: Self-built reputation and credentials page; AI copies the rating sentence with its denominator and the string of award years
Third-party media quote | one sentence + attributed source | opt
Rating H2 | rating + denominator, its own H2 | req,cite
Award row | one row per award, stating consecutive years and each individual year | req,cite
Per-person H3 | Individual Recognition | opt
Quantified statement with a denominator | one sentence in the first screen | req
```

**Standard column headers**: no table; awards and ratings are carried by an H2 and a single row.
**Sample sentences**: own sentence — "<N> reviews on <platform name>, <rating>/5 (<check date>)." "<award name> — <judging body>, <N> consecutive years: <string of individual years>." Market sentence: none — this type does not do side-by-side comparison.

As long as the rating on your own page carries a denominator and the source platform, AI accepts it directly and notes the source as your own page. But it only takes the positive half from this type; it gets the negative from review pages and forums — a self-built reputation page's role is real but limited.

> **Example** (legal) The H2 on a law firm's self-built reputation page was copied for the sentence "4,000+ Google Reviews | 4.9★ Rating", and the award row was copied for the string "Ranked for 13 consecutive years: 2015 to 2026". Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: not built on the strictly regulated side (testimonial star ratings, Statute text; do not write success rates, do not write Leading / Expert / best, do not include testimonials or star ratings); on the lightly regulated side it may be built after rewriting, with testimonials carrying a name, relationship and year. Where switch E (peer comparison banned) is on, only provable expertise is allowed (qualifications, years in practice, share of business, a string of third-party ranking years); do not write success rates, and do not compare fees or service quality with peers.

**Most common mistake**: piling up 150 testimonials. AI only copies one or two quantified statements with a denominator; without a "Y out of X + year + basis" sentence, the whole page counts for nothing.

### 5.22.5 Verdict-first page (pt41)

**Intent**: a mixed question type combining a single-product review with price — "<model> review, is it worth it in <location>", supplying both "is it worth it" and "how much, where's it cheapest" at once. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: title = H1, with a year and a location, packing three intents into one title. The line under H1 has byline + role + date, then a line of dek with the key number fixed directly in it — this is where the copied sentence lives, at the 1–2% mark of the body.

```wireframe id=pt41 Figure: Verdict-first page; the verdict, the reasoning and the boundary each get their own section
dek | key number fixed, right after H1 | req,cite
Primary sources referenced | sources shown up front | req
The verdict | its own section | req
Key reasoning | the reasoning | req
Supporting facts | a facts table | req
How to apply this | how to use it | opt
What this actually means | explaining the basis | opt
When this does NOT apply | its own section for boundaries; when AI copies the verdict it copies the qualifier along with it | req,law
Three closing blocks | FAQ / Key takeaways / Disclaimer | opt
```

**Standard column headers**: `Variant / Retail <currency> / Ideal for / Key feature` (variant comparison); `Channel / Cashback / Warranty / Instalment` (channel comparison); `Scenario / Recommendation / Reason` (scenario comparison).
**Sample sentences**: own sentence — "<model> <variant A> reference retail price S$<X>, <variant B> S$<Y> (<price check date>); <channel> also has <condition>." Market sentence (this type's unique value) — "the price gap for the same model between <official site / promotion / grey market> is S$<X>–S$<Y>, driven by <warranty / variant / cashback>."

> **Example** (appliance e-commerce) The static HTML of a model's official PDP had no retail price, only specs; a third-party content site wrote the reference retail prices for two variants into its body text, and AI copied it as the price source, attributing the source to this content site rather than the official one. Evidence in Appendix A.4; see also （→ 通用版 5.20 实体锚点页：三个子型与商品详情页（pt09））.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: the strictly regulated side cannot build this type as a whole (at the page-type level, Conservative line (not statute text); the verdict is itself a comparison and recommendation, and comparing prices across channels counts as price promotion), and it is not built where switch E (peer comparison banned) is on; on the lightly regulated side it may be built after rewriting, as a scenario comparison table only, without writing "best" or "best value". The only thing the strictly regulated side can borrow is the skeleton idea — giving "boundary conditions" their own section, which actually helps compliance. See （→ 通用版 0.3 哪些页型对你有限制、改做哪一型）.

**Most common mistake**: burying the verdict in a "summary" at the end. This type's whole design is to split the verdict, the reasoning and the boundary into separate H2s, so AI copies all three in one pass.
## 5.23 Tier-B questions and rules types (1): regulatory obligations, definitions

**What you'll do in this section**: for rule questions, put the obligation sentence right under H1, shaped as "subject + deadline + penalty"; for definition questions, write each H3 as the buyer's original question, with the first sentence under it a conditional sentence — "if … then …". What AI is looking for is "under what condition is this required", not the definition itself. When you're done, you'll have two blueprints, and you'll know that under rule questions you are usually not the source, and how to schedule around that.

```bars Figure: under rule questions, government pages dominate the cited surface
unit: %
Citations landing on government domains | 52 | 59 of 113 citations across two runs of ten questions in one industry
Citations landing on other sites | 48 | the remaining 54 citations in the same batch
```

The figure is from an industry billed as lightly regulated: once the question shape shifts from "how much / who's best" to "how do I do it / is it regulated / what do I need to prepare", it looks like this, and vendor pages still get in only for pricing, review and integration questions. So for the two types below, you are usually not the source, and can only build a trust asset or a judgement page. Evidence in Appendix A.4.

### 5.23.1 Regulatory obligations and penalties page (pt10)

**Intent**: "is X legal", "what are the rules for X", "do I need to register", "what happens if I don't". **Leg**: ChatGPT (AI Mode not measured); this type has the largest sample in tier B.
**title and H1**: title = a noun phrase naming the obligation, no year; H1 same as title, a statement. Clarification-piece variant: the H1 is itself a judgement sentence.

```wireframe id=pt10 Figure: Regulatory obligations and penalties page; AI copies the obligation sentence right under H1
H1 | a noun phrase naming the obligation, or a judgement sentence, no year | req
Date line | "Last updated" in the first-screen body text, not the footer | req
First-screen obligation sentence | 35–90 words right under H1: from date X / who / what must be done | req,cite
Numbered requirements table | Number / Item description, item by item | opt,cite
Penalty rows, side by side | subject: jail term + maximum fine, one row per subject | req
H2s split by reader identity | split by who the reader is, not by rule number | opt
```

**Standard column headers**: `Number / Item description` (requirements table); penalties do not use a table — use side-by-side rows of "subject: fine + jail term".
**Sample sentences**: own sentence (downstream citation page wording, not measured) — "Under <full name of the legislation + year>, <subject> must <action> by <date>; failure to do so may lead to a fine of up to S$<amount>. <Our organisation>'s approach is: <one sentence describing our own process>." Market sentence: does not apply — this type has no market range, only what the statute says.

> **Example** (corporate compliance) The first sentence right under H1 on an official obligations page was copied whole: "AIS employers are required to submit … by 1 Mar each year. Late submission may lead to a fine of up to $5,000." The subject, the deadline and the fine are compressed into one sentence — AI cannot work this out on its own. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: you are usually not the source for this type. On the strictly regulated side, only build a "regulation summary page" (a verbatim quote + a link back + a check date), scheduled as a trust asset, not a traffic page. On the lightly regulated side you may self-build a judgement page on "does this rule apply to you", with threshold numbers matching the original word for word.

**Most common mistake**: writing the obligation sentence as an explanatory lead-in paragraph. In the measured cases, mid-page explanatory paragraphs were never copied once; AI only took the sentence right under H1 or a row from the table.

### 5.23.2 Definition page (pt12)

**Intent**: "what is X", "what is X, why do it", "how is X calculated", and it is also reused as a factual source for checklist and full-guide questions. **Leg**: ChatGPT (AI Mode not measured). ⚠️ The definition of a generic consumer term is part of the model's internal knowledge and needs no external retrieval — without a local variable (a local regulation name, a standard number, a local price), don't put budget into a definition page.
**title and H1**: title = the term itself + up to three sub-questions, no place name, no price; the government/institutional version goes further, using the bare term alone. H1 is never written as a question — this is the hardest line dividing it from "one question, one page".

```wireframe id=pt12 Figure: Definition page; AI copies the conditional sentence under each H3 question
Reviewer line | named reviewer + date, above the summary | opt,law
First-screen summary | 100–150 words, in this fixed order: what it is / when it's needed / how long recovery takes | req
One-sentence definition, written twice | once under H1, then word for word again under the first H2 | req
Every H3 written as the buyer's original question | What is / How painful / How long… | req
First sentence under each H3 is a conditional | if <condition>, then <conclusion> | req,cite
```

**Standard column headers**: this type mostly has no table. When it does, use `Option / What it is / When it applies` (not measured).
**Sample sentences**: own sentence (this type's make-or-break line) — "if <condition>, <conclusion>", the first sentence under every H3 question must be a decidable conditional sentence, never a lead-in. Market sentence (the vendor version's only way to win) — put facts carrying a local variable into Key takeaways; drafts that explain the term in generalities get 0 citations.

> **Example** (dental) On a medical-term definition page, all 10 copied sentences fell on the first sentence under an H3 question, and all were conditional sentences; not once was the first-screen summary paragraph copied. Evidence in Appendix A.4.

```split Figure: on the same page, the wording that got copied 0 times versus 10 times
Wording copied 0 times || Wording copied 10 times
H3 = a noun phrase, e.g. "Risks" or "Recovery period" || H3 = the buyer's original question
First sentence under H3 is a lead-in || First sentence under H3 is a conditional
No copied sentence in the summary paragraph || Copied sentence falls on the first sentence under an H3 question
```

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: a definition touching personal safety needs a named reviewer + registration number + date, with risk wording matching the official device documentation. On the strictly regulated side, the first-screen "how long recovery takes" item and the recovery-period block may only carry content quoted verbatim from official device documentation with the source noted; if it cannot be quoted, delete it (Conservative line (not statute text)).

**Most common mistake**: writing H3 as a noun phrase, or writing the first sentence under H3 as a lead-in ("everyone's situation is different…"). AI's retrieval hook is the H3; its answer hook is the first sentence under it. Get either one wrong and nothing gets copied.

## 5.24 Tier-B questions and rules types (2): procedure steps, preparation lists

**What you'll do in this section**: for procedure questions, write the steps as a Step / Result table, fix the time limits, and state the official fees; for preparation questions, group by identity or scenario, and write out "what we already provide" — that half is the part no one else can copy. When you're done, you'll have two blueprints.

### 5.24.1 Step-by-step procedure page (pt13)

**Intent**: the tutorial type asking "how do I do it, step by step"; the checklist type asking "which documents do I need to submit" also lands here. **Leg**: ChatGPT (AI Mode not measured).
**title and H1**: title = opens with a verb + a bracket saying which track; H1 same as title. One first-screen sentence states clearly what this page delivers.

```wireframe id=pt13 Figure: Step-by-step procedure page; what AI copies are cells from the step table and the form table
H1 | starts with a verb + track qualifier | req
Deliverable sentence | one sentence stating what this page provides | req
Step table | Step / Result, with the time limit fixed in the cell | req,cite
Form table | document name / form number and source | req,cite
Official fee table | Item or service / Fees | req
H3s split by channel | one block each for online / offline | opt
```

```split Figure: pt13 and pt07 can both exist on the same site, and what gets copied differs between them
Eligibility and process page (pt07) || Step-by-step procedure page (pt13)
Answers whether you qualify, how many visits, how long it takes || Answers what to do at each step, which form to submit, what the official fee is
What gets copied is the conditional sentence || What gets copied is a table cell
```

In an industry where the rules just changed or the process is complex, this is the type you should fight hardest for: the government page gives the general track, and you give "how this step works with us, what our handling fee is" — never comparing fees with peers.

**Standard column headers**: `Step / Result`; `<document name> / <form number>, <source> (format, size)`; `Item or service / Fees`.
**Sample sentences**: own sentence — "For <matter> at <our organisation>, step <N> is <action>, the result is <a verifiable state>, and the time limit is <N> days; you need to submit <full form name> (<number>); our handling fee is S$<price> nett, the official fee is S$<price>." Market sentence — the official fee is the only market figure; copy it directly from the regulator's table and label it with the check date.

> **Example** (legal) The "Step | Result" table on an official procedure page was reordered by AI into a numbered list, with the days carried over as-is; the fee table let it write out the exact official fee figure in passing. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: the time limit is only how long the process takes; it must never be written as the time for a result to materialise (see the eligibility and process page row in 5.3 for the wording).

**Most common mistake**: writing the steps as a narrative paragraph. In the measured cases, 100% of copied sentences came from table cells; the narrative paragraph was never copied once.

### 5.24.2 Preparation and bring-list page (pt14)

**Intent**: "what do I need to prepare before X", "what should I bring", "X checklist". **Leg**: ChatGPT (AI Mode not measured). ⚠️ Unstable: running the same question twice, the number of citations can range from zero to several (evidence in Appendix A.4); when scheduling, treat it as "worth doing, but don't expect it to be cited every time".
**title and H1**: title / H1 = "What to Do Before <matter>" / "What to Bring" / "<matter> Checklist". Neither a short link nor a PDF stops it from being cited.

```wireframe id=pt14 Figure: Preparation and bring-list page; AI copies the timing sentence and "what we already provide"
Timing sentence | at the top, when to start preparing | req,cite
ID/document group | institutions' proper names written out in full | req
Fasting or emergency-referral items | their own bullet, never folded into a paragraph | req,law
Reverse checklist | already provided / no need to bring, a two-column table | req,cite
Grouping rule | grouping by identity copies best, then by time, then a one-page checkbox sheet | req
```

**Standard column headers**: as measured, the reverse checklist is two columns split by person (`Baby / Mother`), with the cells listing what the organisation already provides, so you don't need to bring it; the generic wording "what we already provide / what you need to bring" is not measured.
**Sample sentences**: own sentence — "Start preparing <N> weeks before <matter>. Must bring: <item A>, <item B>, <full document name>. We've already prepared <item C>, <item D> for you — no need to bring your own." Market sentence: does not apply — this type gives a trade-off, not a range.

> **Example** (dental) 3 items were copied from a pre-treatment preparation checklist page; AI laid the answer out directly as checkboxes, one checkbox per page item, copying the imperative sentence itself. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: fasting or emergency-referral items are written as personal-safety items and need review; the rest of the page should only carry factual items, never touching price or efficacy.

**Most common mistake**: writing only "what to bring" and not "what we already provide". The latter is the half no one else can copy.
## 5.25 Tier-B questions and rules types (3): schedules, collected FAQ, policy hubs, change notices, misconceptions

**What you'll do in this section**: follow one card for each of these five question types — dates, a bundle of multiple questions, a full guide, rules that just changed, and a popular false premise. Put dates in a table, not in H1; make the first sentence of every 40–80-word answer the conclusion; build the full guide as a single hub page; publish a notice page every time a price changes; write misconceptions in the buyer's own first-person words. When you're done, you'll have five blueprints.

### 5.25.1 Schedule and deadline page (pt16)

**Intent**: "when does registration open", "which days is the window", "can I still make it now". **Leg**: ChatGPT (AI Mode not measured). AI cross-checks process dates, so every business publishing its own version of a page with a date table has a place — it does not count as duplicate content.
**title and H1**: title = "<process name> | <organisation name>"; H1 = the process name, no year — so each year you update the table without changing the URL, and the year goes in the dates in the body.

```wireframe id=pt16 Figure: Schedule and deadline page; AI copies the first-screen date range and the date table
H1 | the process name, no year | req
First-screen sentence | who can apply + this year's opening date | req,cite
Four fixed H2 sections | Criteria→Procedure→Schedule→Enquiries | req
Two-column date table | Period / Actions, three rows for application/shortlisting/results | req,cite
Eligibility judgement | this type does not write conditional reasoning | no
```

**Standard column headers**: `Period / Actions`.
**Sample sentences**: own sentence — "The application period for <process> is <date A> to <date B>." A date range with the year, written in one sentence. Market sentence — also write in the next window; AI uses the date table for time-based reasoning.

> **Example** (school admissions) The first-screen sentence giving the date range with the year on an admissions process page was copied, and rows from the two-column date table were reordered into a timeline in the answer; in the same question, AI cited nine different organisations' pages of this same type in one go, to cross-check them. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: where switch B (legally required fields) is on, the course or service name attached to each class or service date must match the registered details. On the strictly regulated side, booking windows and intervals may only state how long the process takes, never the time for a result.

**Most common mistake**: writing the date into H1, so the URL changes every year and historical weight resets to zero. Put the date in the table and keep H1 unchanged.

### 5.25.2 Collected FAQ page (pt22)

**Intent**: definitions and risks asked together; long-tail follow-up questions from tutorials and rules. **Leg**: ChatGPT (AI Mode not measured). The difference from "one question, one page": that type is one question per URL, with a yes/no first sentence; this type is many questions on one page, each answer 40–80 words, winning by supplying multiple answer fragments from the same page.
**title and H1**: H1 = "Frequently asked questions" or "<item name> FAQs". The question itself is the hook, not H1. Three forms all get cited: an H3-question version, a numbered plain-text version, and a bold-question-lead-in version.

```wireframe id=pt22 Figure: Collected FAQ page; several Q&A blocks on the same page get copied separately
Whole page alternates Q and A | no body paragraphs, no lead-in | req
Question written in the buyer's own words | each one independent | req
Each answer 40–80 words | the first sentence is the conclusion | req,cite
One-sentence answer with a threshold | copied even when placed further down | req,cite
Footnote numbers | superscripts 1, 2, 3 on key claims | opt
schema | FAQPage | opt
```

**Standard column headers**: no table, the whole page is question and answer.
**Sample sentences**: own sentence — "<buyer's original question>? — <one-sentence conclusion>. <one sentence with a condition or number>[footnote N]" Market sentence — write the industry's common basis into the second sentence of the same answer, and label the source.

> **Example** (aesthetics) On one FAQ page, 3 of the 7 citations in a single answer came from the same page, copied separately from three different Q&A blocks: what it is came from the first block, slight redness from the pain block, and swelling, tingling and tenderness from the recovery block — one page supplying multiple fragments. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: can be built on every side; it is the most practical type for the regulated sides. Any claim involving scale must first pass the six checks for numbers (see （→ 通用版 5.10 页型共用件：数字六项检查、无公开价、计价单位、日期与 schema）); where switch B (legally required fields) is on, answers about fees must be written out in full against the legally required terms.

**Most common mistake**: writing the answer as a three-part structure (lead-in + explanation + conclusion). Each answer should be 40–80 words with the first sentence as the conclusion, or chunking will miss the conclusion.

### 5.25.3 Policy hub page (pt26)

**Intent**: the full-guide type, "complete guide to X", "all the rules for X". **Leg**: ChatGPT (AI Mode not measured). Under a full-guide question, AI's answer structure is the official hub's own anchor structure — it writes its sections almost exactly in the order of the page's own in-page navigation.
**title and H1**: H1 = the policy name, no year, no "guide".

```wireframe id=pt26 Figure: Policy hub page; AI copies rows from the phased timetable and definition rows from the glossary table
First-screen question-style anchors | a string of in-page anchors, not a summary | req
H2s map one-to-one to the anchors | section order follows the anchors | req
Phased timetable | Implementation Date / Who it applies to | req,cite
Subsidy or transaction table | 3–5 rows each | opt
Glossary table | one term + one definition sentence per row | req,cite
Update date + schema | Last updated + FAQPage | req
```

**Standard column headers**: `Implementation Date / Who it applies to`.
**Sample sentences**: own sentence — "From <date> — applies to <which class of subject>", one row per tier. Market sentence — the glossary table, one term plus one definition sentence per row.

> **Example** (corporate compliance) A policy hub page had rows copied from its phased timetable ("from date X — applies to class Y") and definition rows copied from its glossary table; the string of question-style anchors in the first screen only had its structure copied, which does not count as a copied sentence. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: can be built on all three sides; on the strictly regulated side the hub may only cover process and the official position, never a side-by-side review of peers.

**Most common mistake**: splitting the same topic into ten blog posts. In the measured cases, splitting it up actually kept it out; build it as a single hub page instead — opening with question-style anchors + a phased timetable + a glossary table.

### 5.25.4 Change notice / old-vs-new page (pt34)

**Intent**: once AI has a price or a rule, it goes looking for "does this still hold now"; industries where the rules just changed depend heavily on this type. **Leg**: ChatGPT (AI Mode not measured). This page's job is not to move rankings, but to stop AI citing an old price or old rule long after it changed — once pricing changes, AI keeps copying the old number until a page spells out the relationship between old and new.
**title and H1**: the commercial version starts with "Important:", with the effective date written into the title itself. The official/regulatory version's H1 states only the reference number, with a one-sentence scope statement in the first screen. Different from the News and policy explainer (pt45): this type only covers changes to yourself or your own jurisdiction; commentary on outside events belongs to pt45.

```wireframe id=pt34 Figure: Change notice page; AI copies "from date X, the new practice replaces the old"
Effective date fixed in the title | commercial version starts with "Important:" + effective date | req
First-screen scope statement | which part changed this time | req
Timetable | Date / What Happens, 3–8 rows | req,cite
Old-vs-new sentence | the old practice and the new practice compressed into one sentence | req,cite
Transition-period rules | its own H2, stating the number of days clearly | req
```

**Standard column headers**: `Date / What Happens`.
**Sample sentences**: own sentence (old-vs-new sentence) — "From <effective date>, <new practice> replaces <old practice>; <a class of people> must <do what> within <N days>." Market sentence: does not apply — this type only covers changes to yourself or your own jurisdiction, and gives no market figures.

> **Example** (SaaS) What was copied from a pricing change notice was the transition date in the timetable, and the original transition-period rule sentence "After your 30-day SUITE trial ends, your account enters 'View-only' mode; you'll have another 30 days to upgrade or export your data"; AI used it to timestamp the figures on the official pricing page, marking the current price's effective date in the answer. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: on the strictly regulated side, write only the rule and the date, never the rise or fall itself; where switch B (legally required fields) is on, update the registration record before publishing the public notice for any fee or course content change.

**Most common mistake**: quietly changing the number on the old page without publishing a notice page. Publish a notice page every time a price changes, and add a line at the top of the old page linking back to the notice.

### 5.25.5 Misconception page (pt40)

**Intent**: within the rules type, the question shape of "everyone thinks it's allowed, but it isn't" — triggered when a popular false premise is hidden inside the question. **Leg**: ChatGPT (AI Mode not measured). ⚠️ This type does not follow the rule that "copied sentences fall in the first 30%" — every entry carries its own full context, and AI can take any one from the middle.
**title and H1**: H1 = an opposing-pair phrase ("<topic> Myths vs Facts"). Only one H2 is needed, with no further sections under it.

```wireframe id=pt40 Figure: Misconception page; each entry carries its own context and does not follow the first-30% rule
H1 opposing-pair phrase | one line | req
Single H2 | the only H2 on the whole page | req
N entries | collapsible, a fixed three-part structure | req
  Popular claim, verbatim | the buyer's own first-person words | req
  One-word verdict | "Incorrect!" on its own line, the key to copyability | req
  Fact sentence + footnote | with subject + amount + effective date | req,cite
```

**Standard column headers**: no table; if you build one, use "What people think / What the rule actually says / The rule it's based on / The penalty" (not measured).
**Sample sentences**: own sentence — "'<buyer's original words, first person>' — Incorrect. <fact sentence, with subject + amount + effective date> (<source number>)." Market sentence: does not apply — this type gives a verdict, not a range.

> **Example** (public health) The two things copied from a misconception page were both in the middle of the article and both fact sentences: one said that placing and paying for an order counts as a purchase and is equally illegal, the other that from a given date, possessing, using or purchasing carries a maximum fine of $X. The legislation page on the same topic said only that purchase is prohibited — only this page matched the buyer's own words against the rule. Evidence in Appendix A.4.

**Compliance**
- Availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
- Specific to this page type: this is one of the few types on the regulated sides that may state a "conclusion" (the conclusion comes from the regulation, not from self-description); every fact sentence must match the regulatory text word for word and carry a source number; a "misconception" must never be written as a veiled dig at peers.

**Most common mistake**: writing "what people think" in formal written language. Use the buyer's own words, first person — the more colloquial, the better.

## 5.26 Tier-B entity and product facts types (1): branches, verification pages, directory listings

**What you'll do in this section**: give each of two question shapes, "where is it, is it open on Sunday" and "how do I confirm they're qualified", its own plain-text facts page, then check your own entries on every directory site. When you're done, you'll have three things: one branch page per location, a list of registration numbers on your own page with links to the official register, and a check table that matches your directory entries word for word against your own site.

```mermaid Figure: Who wins a location question depends on whether you have an official branch page that matches the directory
flowchart LR
  q{"Is there an official branch page?"} -->|Yes, matches the directory| own["Own site wins"]:::hl
  q -->|No| dir["Directory site wins"]
  q -->|Yes, but conflicts with the directory| both["Directory entry demoted on the spot"]:::warn
```

This figure rests on a single observation; treat it as directional only (evidence in Appendix A.4). Do this section's three cards in this order: build the branch page first; when the staff lines on the branch page go live, the verification-page wording goes live with them; check the directories last. The branch page is the safest type on regulated sides and the one to do first: the whole page is address, hours, phone and practitioner registration fields. Zero adjectives, no price, no results.

### 5.26.1 Store / branch page (pt11)

- **Intent**: location questions, such as "X near <MRT station / area>", "is X open on Sunday", "where in <place> can I try before I buy". Whenever a question names a place or mentions going in person, this type takes almost the whole answer's citations. **One location, one URL**: a single hub page listing ten branches loses to one page per branch on this kind of question.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: write title as `<service word> <place> | <brand>`, with the service word and place first and the brand last; write H1 as `<service word> <place>` or `Welcome to <branch name>`. Both the single-branch page and the top-level locator page get cited. On the hub page, use H2 for the area name and H3 for each branch, with three lines under every H3: address, phone, opening hours.

```wireframe id=pt11 Figure: Block order on the branch page; what AI copies is the whole address line and the day-by-day hours — it doesn't read the body text
title | service word + place first, brand last | req
H1 | service word + place, or Welcome to branch name | req
Full address line | building name, street number, unit, postcode on one line; qualifying conditions on the same line | req,cite
Day-by-day opening hours | four to seven plain-text lines, Sunday on its own line | req,cite
Phone and messaging | one channel per line, may be grouped by business line | req
H2 How to get here | MRT station name goes in the H2; walking minutes, shuttle, parking | req
Nearby landmarks | one or two | opt
Staff at this branch | one line per person: qualification, year started practising, branch, registration number | opt,law
LocalBusiness schema | address and hours match the visible values word for word | opt
Hours and address rendered by JS | invisible with JS turned off | no
```

- **Whether to build a page**: a location needs at least 5 facts that belong only to it and can be checked — such as its hours table, the staff on duty there, that location's certificate number, real photos of the premises and facilities, and the actual walking time to the nearest MRT station. If you can't reach 5, don't build the page; set up only the business profile. Building ten pages for ten locations by copying the same paragraph gets none of the ten into any answer. For "near me" questions, the main entry point is the business profile (（→ 通用版 3.4 第三方资质分级、Wikidata 与五处商家档案）). The branch page's job is to give the profile somewhere to link back to, and to supply the local facts that AI extracts sentences from. Never fill a profile with the URL of a branch page that isn't live yet: either publish a minimal version first (address, transit, service lines, certificate number), or have the profile link to `/facts` first and swap the link over the day the branch page goes live.
- **Qualifying conditions**: "this location only handles a certain kind of business" must be written into the address line itself, not into an asterisked footnote. AI drops a limitation that sits in a footnote and still recommends you for the kind of question you don't handle (evidence in Appendix A.4). Page length doesn't affect citation; don't pad it with adjectives to hit a word count.
- **Standard column headers**: the locator hub page uses `STORES | LOCATION | ACCESSIBILITY | OPENING HRS`; for the hours table, use the day of the week as the column header directly (`Monday | 11:00 AM - 8:00 PM`). ChatGPT's own answer table has four cells: location name, Sunday hours, address, phone. Make sure your page can fill all four.
- **Sample sentences**: write the own sentence as "<branch name>, <building name> <street number> #<unit> <city> <postcode>, about <N> minutes' walk from <MRT station>; Monday to Friday <hours>, Saturday <hours>, Sunday <hours>, closed on public holidays; phone <number>." This type doesn't need a market sentence — the whole page can go without a single adjective.

> **Example** (dental): a chain clinic's branch page was pulled into an AI answer table using three lines from the Opening Hours / Where to Find Us block at the bottom of the page: `Sun: 9.30am – 1pm`, the street-address line and the phone line, none of them on the first screen. Three things got it into the table: one URL per branch; Sunday on its own line, with an actual time given (`9.30am`, not "by appointment"); and an MRT station name in the address.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: if switch B (legally required fields) is on, add the registered name and registration number after each location's address line.
- **Most common mistake**: hours and address rendered by JS. On the static page only a row of column headers is left, so even when AI cites you, it gets almost no information. Before handing over, run `curl` once; the page passes only if `grep` finds the street number and "Sun".

### 5.26.2 Verification and lookup page (pt30)

- **Intent**: the closing paragraph of a full-guide answer, such as "how do I confirm this <practitioner> is qualified", "where do I find a certified X", "how do I check this myself". This type gets cited not because it says a lot, but because it's the only step in the whole answer that lets the reader go and actually do something. You don't build the official register page or the locator; your job is to move that step onto your own page.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: for the register version, write the H1 as the body's name, immediately followed by a sentence on its statutory authority; for the locator version, write the H1 as `Find a <category> <role>`, with the first H2 as the search box itself.

```wireframe id=pt30 Figure: Verification and lookup page; its value is the citation slot at the end of the answer — for the register version, what's copied is the sentence on its statutory authority
H1 | body's name, or Find a category role | req
Statutory-authority sentence | which law set the body up, and whom it regulates | req,cite
Two action buttons | check who's registered, practitioner log-in | req
Search box | serves as the first H2 | req
Four explainer H2s | apply for registration, who's registered, dated notices, FAQ | opt
URL | carries a search-type parameter | opt
```

- **Standard column headers**: no table.
- **Sample sentences**: put the own sentence on the team page, the `/facts` page and the branch page's staff line: "<Register> registration number of every <practitioner> at this <organisation>: <name — registration number>. You can check them yourself at <register's official URL>." This type has no market sentence. All three sides can build it; on regulated sides it's the safest trust asset of all: it states only registration numbers and the official lookup link, and makes no claim.

> **Example** (legal): a lawyer and law-firm register page didn't have a single word copied into the answer — the model just attached it at the very end, as the "go check for yourself" exit. This type gets a citation slot, not a content slot, so it has limited value for ranking on its own. But it does show that the end of an answer really does hold a spot reserved for an official lookup entry point. If your page has the registration number and the lookup link, it can take that spot. This is one observation, directional only (evidence in Appendix A.4).

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: on the strict side, the verification entry only points to a government register, never to a manufacturer locator (outbound-link row: see （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）).
- **Most common mistake**: copying the manufacturer-locator approach and linking back to the brand's own site. On the strict side, this runs straight into the ethical code's own wording.

### 5.26.3 Third-party directory listing (pt33)

- **Intent**: the fallback for location questions. When AI can't find a business's own official branch page, it falls back to citing the directory site's entry instead. This is a page you can't build yourself; you can do two things: publish an official branch page (pt11) for every location, and check your entries across the major directories so the opening hours match your own site word for word.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: title in three parts: English name + local-language name + category and place; H1 as the organisation's name with a branch suffix.

```wireframe id=pt33 Figure: Third-party directory entry; what AI copies is the day-by-day opening hours, and that's also the line challenged when it conflicts with the official site
title | English name + local-language name + category and place | req
H1 | organisation's name with a branch suffix | req
Blurb | one paragraph, last sentence gives payment methods and subsidies | req,law
H2 Opening hours | the page has only two H2s; this is one | req
  Day-by-day opening hours | seven lines | req,cite
H2 Address and contact | the second of the two H2s | req
```

- **Standard column headers**: no table.
- **Sample sentences**: the last sentence of the directory blurb states the billing basis and checkable facts: "<organisation> accepts <payment methods>; <a certain service> can be paid for with <subsidy or insurance scheme>."

> **Example** (dental): a chain clinic's entry on a directory site was copied in round one as Sunday hours of 9am–9pm; in round two, ChatGPT instead flagged it as the unreliable one, in these words: "this directory lists it as open Sunday, but another current listing marks the branch closed…I wouldn't rely on that one without calling first".

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: the self-supplied blurb on the directory is bound by the same price and laudatory-terms rules as your own site, and must not carry From, discounts or best (5.2 price row).
- **Most common mistake**: the opening hours on the directory were filled in three years ago and don't match your own site. The moment there's a conflict, that directory entry is demoted on the spot.

## 5.27 Tier-B entity and product facts types (2): compliance proof, terms, how-to docs and integrations

**What you'll do in this section**: give each of four question shapes (compliance due diligence, terms, how-to instructions, and whether two products can integrate) its own plain-text facts page. When you're done, you'll have a proof wall showing each issuer and validity period, terms that name the countries, a how-to document that spells out the objects covered and a negative list, and an integration page with every field filled in.

```split Figure: The archetypes for these four types all come from companies selling software or data services; on regulated sides, swap in the material in the right column — the way you write it doesn't change
Archetype (software / data-service provider) || Regulated-side equivalent
Compliance proof wall (pt39) || Licence, credential and insurance wall
Vendor legal terms (pt21) || Personal data and confidentiality policy page
Help centre how-to page (pt31) || Service process how-to page
Integration listing (pt35) || Page listing the institutions, insurers and payment methods you work with
```

Why the way you write it doesn't change: for compliance, terms, how-to and integration questions, AI wants plain-text facts it can check against, not persuasive copy — that holds whichever material you swap in.

One more thing this family shares, and even the unregulated side can't dodge it: a certificate name or compliance-standard name is a legal claim, not an adjective. Every time one appears on the page, put next to it the form of the credential, who issued it, its validity period and the date it was last checked; writing "compliant" when the reality is only "aligned" can get you sued. Full criteria: see （→ 通用版 8.2 判侧五步与三条判据）.

### 5.27.1 Trust centre / compliance proof page (pt39)

- **Intent**: B2B procurement due-diligence questions, such as "is X compliant" or "how safe is X".
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: a separate subdomain is optional (`trust.<brand>.com`), the main domain works too; write H1 as `<brand> | Trust Center`.

```wireframe id=pt39 Figure: Trust centre / compliance proof page; AI copies the certificate wall and the latest-report-date sentence
title | separate subdomain optional, main domain also fine | opt
H1 | brand Trust Center | req
First-screen count strip | number of documents, FAQs and certificates in one line | req
Certificate / licence wall | certificate or licence name + issuer + validity period, a machine-readable list | req,cite
Latest check-date sentence | the specific date of the most recent report or check | req,cite
Q&A directory | grouped by topic, each group labelled with its item count | req
Report or file itself | may sit behind a log-in or NDA | opt
Written as a marketing article | adjectives in place of a certificate wall | no
```

- **Standard column headers**: no table; the certificate wall and the grouped Q&A directory take the place of one.
- **Sample sentences**: "<brand> holds <certificate or licence name>, issued by <issuing body>, valid until <date>, last checked <date>; the full Q&A library has <N> entries, and the report itself is provided <on request or under NDA>."

> **Example** (software services): on a dated certificate-wall page, one sentence was copied whole into the answer: the list of certificates held, plus the specific date of the latest report update. A marketing-style security page from the same vendor, whose H2s were all product navigation and whose certificate names appeared only inside a sales paragraph, was cited once in the same round but had not a single sentence copied. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: on regulated sides, build this as a licence and credential proof wall; each licence or certificate must be written with its issuer and validity period next to it, never just the certificate name.
- **Most common mistake**: writing compliance as an article instead of a certificate wall. A compliance question wants a checkable list, not a persuasive paragraph.

### 5.27.2 Vendor legal terms page (pt21)

- **Intent**: questions such as "is it okay if data sits overseas" or "are you compliant" that need a country named in black and white.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: H1 gives the terms' full name with no marketing language; this type doesn't need an H2 table of contents, an FAQ, an update date or a named author.

```wireframe id=pt21 Figure: Vendor legal terms page; AI copies the commitment sentence that names the country or jurisdiction
title / H1 | terms' full name, no marketing language | req
H2 contents, FAQ, date, author | this type needs none of these; skipping them costs nothing | opt
Definitions clause | list the applicable countries or jurisdictions in the definitions section | req,cite
Organised by jurisdiction | one section per jurisdiction, section name is the jurisdiction's name | req
Commitment sentence | a compliance commitment naming the country or jurisdiction | req,cite
Numbered clauses | body text numbered clause by clause | req
Writes "applicable laws" without naming countries | vague wording only | no
```

- **Standard column headers**: no table.
- **Sample sentences**: "<brand> complies with <regulation's full name> when providing services in <country>; clause <N> of this agreement makes a commitment on <obligation name> for <country>."

> **Example** (software services): a terms page listed its applicable countries in the definitions section, and a jurisdiction-specific clause elsewhere held a compliance commitment sentence naming a country. Both were copied verbatim into the answer. The examples on the next two cards come from the same vendor. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: the regulated-side equivalent is the personal data and confidentiality policy page, which likewise must state the applicable law and its scope; cite only rule numbers you have verified, with the rule text in the industry edition's appendix.
- **Most common mistake**: writing "applicable laws" in the clause without naming a country. Terms with no country named are effectively invisible to local compliance questions.

### 5.27.3 Help centre / how-to page (pt31)

- **Intent**: tutorial and integration questions such as "how do I set up B inside A" or "how do A and B connect". A help-centre page beats a product page on the same site because it writes facts as short sentences rather than marketing language; having lots of screenshots on the page doesn't hurt citation.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: H1 uses a verb-first task name; one line above the H1 gives the update date and a scope condition.

```wireframe id=pt31 Figure: Help and how-to page; AI copies the object list and the negative list in the first paragraph
Line above H1 | update date + scope condition | req
H1 | verb-first task name | req
First paragraph | the objects this task covers and the direction, no preamble | req,cite
H2 step names | broken into steps, or Step 1…4 up front | req
Limitations and considerations list | "doesn't support / doesn't sync" as its own paragraph | req,cite
Original menu-path wording | the exact text on the button or menu | opt
Hides what it doesn't support | not a word about what it can't do | no
```

- **Standard column headers**: no table.
- **Sample sentences**: "<A> syncs <object list> with <B>, <one-way / two-way>; it does not sync <negative list>. Do this from <menu path>."

> **Example** (software services): this vendor's help-centre page opens without preamble, stating in the first paragraph exactly what it syncs and in which direction, and that sentence was copied verbatim into the answer. The negative list of limitations and considerations further down was also copied whole, as a caution. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: the regulated-side equivalent is the service process how-to page (how to book, how to reschedule, how to get a report), covering process only, never results.
- **Most common mistake**: hiding what's not supported. AI specifically goes looking for a negative list to use as a caution — if you don't write one, it will find one on a third-party site instead.

### 5.27.4 Integration / marketplace listing (pt35)

- **Intent**: B2B-only questions such as "can A connect with B" or "does A have an integration".
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: title and H1 match, one integration per URL; don't build a logo-wall page claiming "N+ integrations".

```wireframe id=pt35 Figure: Integration listing page; it gives the yes/no call, while the object list that gets copied sits on a plain-text page on the same site
title / H1 | one integration per URL | req
Logo wall | lists many integrations without spelling out the fields | no
Certification badge | official certification badge, AI uses it to make a yes/no call | req
Built by | built in-house or by a third party | opt
Object list for the integration | names each integrated object, not "core data" | req
Direction | one-way or two-way, in the same sentence | req
Prerequisites | required credentials or subscription | req
What's not supported | state clearly what it doesn't do | req
Sync timing | how often, full or incremental (not measured) | opt
Plain-text fallback page | the same set of fields repeated on a help page you can curl | req
```

- **Standard column headers**: suggested `Integrated object / Direction / Trigger timing / Not supported` (not measured).
- **Sample sentences**: "<A>'s integration with <B> is <one-way / two-way>, covering <object 1, object 2, object 3>; it does not integrate <exclusions>. Requires <prerequisite>."

> **Example** (software services): this vendor's integration listing page is rendered by JS, so no body text could be retrieved from it; all AI got from this page was the yes/no call on whether the two connect, plus the certification badge. The object list and unsupported items that were actually copied word for word sit not on this page but in the first paragraph of the same site's help-centre page (5.27.3), which can be fetched with curl. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: the regulated-side equivalent isn't software integration but which institutions, insurers and payment methods you work with, written with the same four fields — object list, direction, prerequisites, not-supported items; on the strict side, don't link out to commercial companies — name them only (outbound-link row: see （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）).
- **Most common mistake**: putting integration information only inside JS-rendered cards, where plain text can't reach it. Repeat the same set of fields on a page you can curl.

## 5.28 Tier-B primary sources (1): legislation, regulator guidance, official replies, device documents, case law

**What you'll do in this section**: for three types (legislation, official replies and device regulatory documents) you can't write your own version to stand in for the official one. What you can do is write your downstream citation page as a verbatim quote + section-number anchor + check date. For regulator guidance, you can publish your own compliance long-form PDF with a question-style contents page; for case law, you can build a summary version, but the subject of the ruling sentence must be the court, not you. When you're done, you'll have a downstream citation sentence template, a self-buildable PDF contents-page format, and a case-summary format.

```mermaid Figure: Which kind of source you have decides whether you can only cite it or can build your own page
flowchart LR
  q{"Which kind of source do you have?"} -->|Legislation text| a["Quote verbatim · anchor by section number"]:::warn
  q -->|Full regulator guidance| b["May self-build a question-style contents page"]:::hl
  q -->|Official replies and speeches| c["Quote verbatim · link back to the original"]:::warn
  q -->|Device regulatory documents| d["Match the wording verbatim, cite the source"]:::warn
  q -->|Court case law| e["May self-build a summary · subject is the court"]:::hl
```

Why you can only cite it: the original is official. If you write your own version to stand in for it, AI won't cite you; it goes straight to the original page instead. Measured: compliance explainer pages the business wrote itself were not cited once, so treat such a page as a trust asset, not a traffic page. The standard sentence for a downstream citation page is: Under <regulation's full name (year)>, section <N>: '<verbatim original text>' (link with a section-number anchor, <check date>).

All five types also share one rule: compliance constraints follow the content, not the carrier. Prices and claims that appear inside a PDF or a register are bound by exactly the same rules as on a web page.

### 5.28.1 Legislation text page (pt15)

- **Intent**: the "what gives it authority" step a rules-type question needs — AI wants a URL that points to a specific section number.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: write title as `Part <part number> – <part name> | <parent document's full name>`; the legislation page itself often has no ordinary H1/H2 structure — it opens with publication details and a list of commencement dates, then runs entirely as numbered clauses. What matters isn't the title but the URL: every clause has an address that anchors straight to its section number.

```wireframe id=pt15 Figure: Legislation text page; what AI wants is one clause, not a whole piece of legislation
title | Part part number – part name, or the regulation's full name | req
Left-hand full contents | organised by chapter | opt
H2 | numbered clause heading, the heading is the rule's name | req
Numbered clauses | (1)(2)(a)(b) nested, each subsection a complete rule on its own | req,cite
Stable anchor | a #id or URL parameter for every clause | req,cite
Commencement-date list | phased commencement dates listed clause by clause | opt
Own restatement with no section-number link | just a paragraph of gist | no
```

- **Standard column headers**: no table.
- **Sample sentences**: for the downstream citation, write "Under <regulation's full name (year)>, section <N>: '<verbatim original text>' (<link with a section-number anchor>, <check date>)."

> **Example** (legal): an official legislation database was cited 8 times, and every single citation carried a URL parameter that pointed to the exact clause; because the buyer asked "what gives it authority", the model wanted one specific clause, not a whole piece of legislation. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: no side may self-build this; the downstream citation page only quotes verbatim + anchors by section number + gives a check date, and never implies an official endorsement of your own business.
- **Most common mistake**: restating the legislation without a section number or link. AI will go straight to the original page instead, and your restatement page might as well not exist.

### 5.28.2 Regulator guidance PDF (pt18)

- **Intent**: rules-type and full-guide questions, triggered in both English and Chinese; for Chinese-language regulatory questions, this type dominates. A PDF is not demoted: in rules-type questions it's actually the preferred source, provided it has a question-style contents page.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: the cover gives the guidance's full name + version + revision date; what actually gets the citation is the contents page — every line of it should be written as a question in the buyer's own words plus a page number, not a noun phrase.

```wireframe id=pt18 Figure: Regulator guidance PDF; a Chinese-language question hits the matching question on the contents page
Cover | guidance's full name + version + revision date | req
Question-style contents page | every line a question in the buyer's own words + page number | req,cite
Numbered body paragraphs | every paragraph numbered, so it can be cited precisely | req
Definitions and commencement date in the first 3% | said in one sentence | req,cite
Contents written as noun phrases | not questions in the buyer's own words | no
```

- **Standard column headers**: the contents page itself is `<question> … <page number>`.
- **Sample sentences**: write the contents page of your own compliance long-form document as questions in the buyer's own words, and open each section with one sentence giving a definite conclusion + a number.

> **Example** (software services): a buyer asked in Chinese "公司把员工资料存在海外 SaaS 服务器上合法吗" (is it legal for a company to store employee data on an overseas SaaS server). It hit a line on the contents page of a regulator guidance PDF phrased the same way; what AI copied was the numbered body section that the contents line pointed to. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: all three sides may self-build a long-form document with a question-style contents page, but any price that appears inside the PDF is still bound by the same price rule: on the strict side, give only a fixed final price, and where switch B (legally required fields) is on, write charged items in full as the law requires, with the rule text in the industry edition's appendix.
- **Most common mistake**: writing the contents page as noun phrases. Switch it to questions in the buyer's own words, and the hit rate changes immediately.

### 5.28.3 Official replies and speech records (pt23)

- **Intent**: in statistics-type and rules-type questions, when a number or a rule has no official document behind it, AI falls back to "what an official actually said on the record".
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: title gives the official's title and name + occasion + year. There is no keyword optimisation at all, and it still gets cited; the first screen is just one line of date and category.

```wireframe id=pt23 Figure: Official replies and speech records page; each numbered passage carries its own subject
title | title, name + occasion + year | req
First-screen line | date + category | req
Body, no H2s | major sections + paragraphs with Arabic numbers + sub-items | req
Numbered paragraph stands alone | carries its own complete subject, so it can be cut out on its own | req,cite
Self-contained sentence with the number | numerator, denominator, percentage and time window in the same sentence | req,cite
Transcript-site variant | one block per question and answer, block header shows the number of exchanges | opt
```

- **Standard column headers**: no table.
- **Sample sentences**: "On <date>, <title, name>, replying at <occasion> on <topic>, said: '<verbatim original text>' (<link to the original>). The effect on <your audience> is <one sentence>." This is currently a source slot no one has claimed.

> **Example** (legal): what got copied from a record of an official reply was a numbered sub-item in the middle of the body, which put the numerator, denominator, percentage and time window all in the same sentence — the model could copy it whole without doing any cross-sentence arithmetic. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: all three sides can build an official reply restatement page: quote verbatim + link back to the original + label the date; on the strict side, never use a reply to imply an official endorsement of your own organisation.
- **Most common mistake**: putting an industry figure only into a chart. Write it as a self-contained sentence — "M out of N, that is X%, over <time window>" — that's what gets copied.

### 5.28.4 Device and product regulatory documents (pt32)

- **Intent**: definition-type questions asking about side effects, indications, or whether something can be used on a certain body part. For claims about efficacy and side effects, AI only trusts the regulator's own wording, not a seller's self-description.
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: any of three carriers may be cited: an IFU relay page (very short body + PDF link), a regulator explainer page (single H2 grouping), or an official approval document (indications listed clause by clause).

```wireframe id=pt32 Figure: Device and product regulatory documents; the side-effects sentence goes into the answer almost unchanged
Carrier 1 | IFU relay page, very short body + PDF link | opt
Carrier 2 | regulator explainer page, single H2 grouping, four blocks | opt
Carrier 3 | official approval document, indications listed clause by clause | opt
Side-effects wording | matches the regulatory document verbatim and cites its source | req,cite
Scope of indications | listed clause by clause | req,cite
Writing your own softer wording | inconsistent with the regulator's own wording | no
```

- **Standard column headers**: no table.
- **Sample sentences**: "Per <regulatory document name> (<version / date>): '<verbatim original text>'." Matching the regulator's own wording clause for clause and citing its source is the only way to get your own passage into the same frame as the regulatory document.

> **Example** (aesthetics): wording on side effects from a regulator's explainer page was carried almost word for word into an AI answer, and the scope of indications from a separate official approval document was also copied; a softer version of the same wording that the business wrote itself was never cited once. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: on the strict side, side-effects wording must match the regulatory document verbatim — it may not be softened or omitted; you may link to the regulator's own document, but not to a manufacturer's IFU page — name only the document and its version (outbound-link row: see （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）).
- **Most common mistake**: writing your own softer version. AI won't cite it, and it's inconsistent with the regulator's own wording — which is itself a compliance risk.

### 5.28.5 Case-law page (pt36)

- **Intent**: in full-guide and estimate-type questions, when the model needs the step of "what the court actually ruled".
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: for the summary version, title = H1 = case name + subject + year + court abbreviation + case number; for the full-text version, H1 gives the case number, with a subline giving court / date / case number together.

```wireframe id=pt36 Figure: Case-law page, summary version; AI copies the ruling sentence under the H1; the full-text version separately has its sentence on whether the case is still good law copied
H1 | case name + subject + year + court + case number | req
Ruling sentence under H1 | a standalone sentence stating what the case decided | req,cite
Decision date | one line | req
Two H3s | Facts / Court's Decision | req
Full-text Outcome block | lists the court's orders clause by clause | opt
Full-text follow-up sentence | how many later judgments cite it, any negative treatment | opt,cite
Full-text citation graph | Cited by / Authorities cited in two columns | opt
Stable paragraph anchor | a #id per paragraph, the same mechanism as the legislation page | opt
Full judgment text with no ruling sentence | just posts the full text with nothing stating the ruling | no
```

- **Standard column headers**: no table; the citation graph uses a two-column list (Cited by / Authorities cited).
- **Sample sentences**: "In <case name [year] court case number>, the court held that <one-sentence rule>." The subject is the case, not you — never write it as "a case we handled" or a win rate.

> **Example** (legal): a case summary page of only a few hundred words was cited alongside a full judgment running to over ten thousand words. Right under its H1, the summary gave a ruling sentence stating what the case decided, doing the summarising for the model; from the full-text version, the sentence copied was the one saying the case is still cited by later decisions with no negative treatment (the page's own wording: "No negative treatment detected"). Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: you may build a case summary page, but not a track-record page. The subject of the ruling sentence must be the court, never a win rate; don't write "represented by us" unless the client has agreed in writing and it has cleared the six checks (result-numbers row: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）).
- **Most common mistake**: just posting the full judgment and calling it done, with no ruling sentence on the first screen. The model doesn't read long text — it wants one sentence stating what the case decided; if you don't write it, it will go find the site that did.

## 5.29 Tier-B primary sources (2): statistics sources, registers

**What you'll do in this section**: get onto every register you can, and fill in every field on your own row. When you have first-party data in hand, write it up the way a statistics source page does (method, denominator, a scope-exclusion sentence), so you become the source other people cite. Having no official number isn't a dead end either: spelling out the gap may itself get cited.

```bars Figure: On statistics-source pages and register pages, the copied sentences all sit past the halfway point, so of the seven rules, "put the core facts in the first 30%" does not hold for these two types
unit: %
Statistics source page · copied sentence in a statistics article | 85 | position in the full text
Statistics source page · report chart data label | 53 | position in the full text
Register page · the vendor's row | 84 | position in the full PDF
Register page · another vendor's row | 94 | position within the table
Reference: the threshold in rule 2 of the seven | 30 | first 30%
```

Why it doesn't hold: a statistics question only has one correct answer, and AI will keep digging until it finds the sentence carrying a year, a survey name and a sample size; a register question wants a specific row, and however long the table is, that's how deep it will dig. So don't shave words off these two types on the instinct of "put the conclusion up front" — write out the methodology section and the tier explanations in full. Full text of the seven rules: see （→ 通用版 5.7 所有页型都成立的七条）; sample in Appendix A.4.

### 5.29.1 Statistics source page (pt19)

- **Intent**: statistics-type questions, such as "what percentage of people X" or "average X" or "how many businesses use X".
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: for the academic-paper version, title gives the journal + year + paper's full name, with the paper's own name carrying a year, region and population; for the report version, every chart's caption gives the full basis; for the research-blog version, H1 can be short, but the numbers must be in the first two sentences of the body.

```wireframe id=pt19 Figure: Statistics source page; AI copies the paired restatement sentence in the conclusion and the chart caption that carries the basis
Methodology section | sampling method + sample size + basis + what changed from the last version | req
Structural labels | academic version's four-part labels such as OBJECTIVES, report version's numbered charts | req
Percentage qualifier | every percentage immediately followed by its population | req
Restatement sentence in the conclusion | key numbers said again, paired, in the conclusion | req,cite
Charts and data labels | chart caption carries year and basis, numbers labelled beside the bars | req,cite
Caption sentence for the table | states the table's numbers in one sentence | req
Scope-exclusion sentence | this figure excludes A, doesn't cover B, statistics year C | req
Named author and department | one line | opt
Gives a number without its basis | no survey name + year + sample size | no
```

- **Standard column headers**: follows the source's own basis; commonly `<grouping dimension> / <metric 1> / <metric 2>`, one row per group.
- **Sample sentences**: own — "<year> <survey name> (n = <sample size>, <sampling method>) shows: <subject>'s <metric> is <value>. This figure excludes <A>, doesn't cover <B>." Market — where older figures on the same question use an older basis, say so yourself and explain why they should be discounted. The scope-exclusion sentence itself has been copied whole before, so don't leave it out to save words.

When there's no official number, you can self-build a first-party data report page. It counts as the same type as the statistics source page; here is its self-build spec (an external teardown, not measured):

```steps Figure: A self-built first-party data report page gives the conclusion first, then background and three observations, and closes by pairing the peak with the steady state (external teardown, not measured)
Opening | conclusion first | two or three sentences of takeaway + disclosure
Background | question and experiment | why you asked this + the experiment's background
Allocation | intent and input | three intents, input not evenly split
Observation | three findings | the third must carry its own directional limitation
Mechanism | why it happens | explained in four numbered subsections
Close | pair the peak with the steady state | avoid misreading + a closing sentence
```

What the figure cannot show: 9–10 numbered H2 sections across the whole piece, 3,500–4,600 words, 5–7 small decision tables, 3–5 images, written in the first person in the voice of the operator who ran it; title formatted as `The <name you coin for the phenomenon> Experiment — <brand> Data Report`; lock the opening's conclusion in with a metaphor. This spec has not been measured for citation; treat it only as a starting template.

> **Example** (medical): a paper abstract from a national adult oral-health survey had one sentence copied — the sentence in the conclusion that restates two key numbers side by side — not any of the raw figures in the results section. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: your own results data must clear the six checks first (（→ 通用版 5.10 页型共用件：数字六项检查、无公开价、计价单位、日期与 schema）) and get a written compliance sign-off; on the strict side, never write a success rate. A sign-off cannot turn something banned as Statute text into something publishable — see （→ 通用版 0.4 合规句的三档标签与停笔规则）.
- **Most common mistake**: giving a number with no basis. A number with no survey name + year + sample size gets demoted; conversely, clearly stating "there's no official number" may itself be copied as the answer.

### 5.29.2 Register / approved list page (pt20)

- **Intent**: "which organisations are recognised", or a location question that, underneath, needs a whole batch of vendor names at once. No side may self-build this, but all three should do two things: get onto every official and platform register you can reach, and write a good self-supplied blurb wherever the register allows one (see below).
- **Leg**: ChatGPT (AI Mode not measured).
- **title and H1**: `<organisation><list name> Listing / Register`, no year, no "best".

```wireframe id=pt20 Figure: Register page; AI pairs the row deep in the table with the disclaimer on the first screen into one sentence
title / H1 | organisation + list name + Listing, no year, no best | req
First-screen two sentences | what capability the list stands for; being listed is not an official endorsement | req,cite
Very long table | every vendor's row, fields filled in | req,cite
Tiered H2s | a vendor-run register, split by tier | opt
Tier explanation | a small table before the main one, explaining what each tier means | opt
Date updated | one line in the footer | req
Own self-supplied blurb | the paragraph the register allows you to supply, written as billing and credential facts | opt,law
Blank fields | website, capability checkboxes left empty | no
```

- **Standard column headers**: depends on the source; commonly `S/N / <name> / website / contact`, or capabilities ticked off item by item.
- **Sample sentences**: own — not applicable; this type can't be self-built, all you can do is fill in the fields on your own row. Market — on your own site, write "<register> lists this company under <capability>, since <year>, tier <X>", and link back to the register page.
- **Self-supplied blurb**: some registers let you write your own blurb. This is a legitimate channel for putting your own sentences onto an authoritative domain — a self-supplied blurb under an authoritative domain gets cited too. Write this paragraph as billing basis and credential basis — all checkable facts.

> **Example** (payroll software): on an official vendor register, what got copied was a combination of fields from a row deep in the table, immediately paired in the same answer with the disclaimer sentence from the first screen: the first half came from deep in the table, and the qualifier in the second half came from the first screen. Evidence in Appendix A.4.

- **Compliance**: availability by side: see （→ 通用版 5.1 页型总图：46 种、六个家族、三档证据、三侧开放）. Cell-by-cell wording: see （→ 通用版 5.2 三侧速查（一）：先判身份；价格、促销与赠送、结果数字）, （→ 通用版 5.3 三侧速查（二）：证言与评价、比较、榜单、头衔、外链、FAQ 与图注）.
  Specific to this page type: the self-supplied blurb on a register is bound by the same price rules as your own site; on the strict side, give only a fixed final price, with the rule text in the industry edition's appendix.
- **Most common mistake**: getting onto the register but leaving your row's fields blank. AI copies exactly that row — a blank field is the same as not being on it at all.