AigeoRadar

AigeoRadar · AI Context Benchmark

AI Context Benchmark

Question → sufficient layer(s) → retrieved slice → measured cost → evidence

WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026

https://aigeoradar.com/blog/wordpress-geo-llms-txt-guide

20 questions Answer LLM: gpt-4o-mini ai_context_benchmark_v1

Of 20 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 8 · AIPM 5 · multi-layer 0 · unanswered 3. Descriptive counts only; no overall ranking.

Of 20 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 8 · AIPM 5 · multi-layer 0 · unanswered 3. Descriptive counts only; no overall ranking. Each question shows: sufficient layer(s) → retrieved slice → measured input tokens → evidence. Readers interpret; the report does not rank formats. Semantic Redundancy 66% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.

Gold mode · Independent HTML gold

Gold answers are derived from the HTML page (title, h1, lang, prose) — not from AIPM fields. Understanding/Retrieval therefore measure layer capability, not AIPM self-consistency. Human-authored gold.json remains the gold standard for publication-grade claims.

Execution provenance

Methodology
AI Context Benchmark Methodology v1.0
Planner Spec
v1.0
Execution Protocol
v1.0
Question pack
universal_v1
Score version
aipm_benchmark_score_v10
Engine
aipm_benchmark_v4
Answer LLM
openai / gpt-4o-mini (single provider this lab)
Model snapshot
2026-07
Run id
c88c8f88-74ca-47d4-8ecb-3d3fb376ee3e

Question outcomes

Per question: which layers were sufficient, and what was the lowest measured retrieval cost among them. No overall winner.

4

Lowest cost: HTML

8

Lowest cost: Schema

5

Lowest cost: AIPM

0

Multi-layer

3

Unanswered

Manifest design

Semantic Redundancy · 66%

Semantic Redundancy 66% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.

  • →Merge or differentiate `purpose` and `abstract` (100% overlap).
Field A Field B Overlap
purpose abstract 100%
abstract title 31%

Structural size (secondary)

Structural size is secondary. A larger AIPM is not a failure if per-question retrieval stays tiny — check Semantic Redundancy instead.

HTML · 22,915 chars
Schema · 11,086 chars
AIPM · 13,294 chars

Routing helper (secondary)

Illustrative card-first vs HTML-always simulation — prefer per-question measured cost above. Not a ranking.

Card-first retrieval would use ~28% fewer tokens than HTML-always on this pack (14 answered from machine card, 6 escalated to HTML). Descriptive only.

Orientation pack

10 questions · all layers scored

  • HTML 10/10
  • Schema 7/10
  • AIPM 7/10

Depth pack

10 questions · all layers scored

  • HTML 4/10
  • Schema 7/10
  • AIPM 7/10

Full-context pack metrics (secondary)

These measure the whole file fed to the model this run — not the minimum slice needed per question.

HTML

14/20 matched

11,540 full-pack tokens

Schema

14/20 matched

8,135 full-pack tokens

AIPM

14/20 matched

8,175 full-pack tokens

Full-pack resource table (secondary)

Whole-file context fed this run. Prefer Minimal Retrieval Cost on each question.

Metric HTML Schema AIPM
Coverage (matched) 14/20 14/20 14/20
Context size 22,915 chars 11,086 chars 13,294 chars
Total tokens 11,540 8,135 8,175
Tokens / correct answer 824 581 584
Est. cost / correct answer $0.000138 $0.000096 $0.000095
Matched per 1k tokens 1.213 1.721 1.713
Median latency 1,525 ms 1,325 ms 1,295 ms
Est. cost (USD) $0.00194 $0.00134 $0.00134

Six independent scores

Answer Efficiency is the primary cost lens. Accuracy axes remain for research — no combined total or winner.

Answer Efficiency

Matched answers per 1k tokens (and cost per match). The primary efficiency axis — not raw accuracy.

  • HTML 70.5
  • Schema 100
  • AIPM 99.5

Understanding

Can this layer convey what the page is about — using independent HTML gold?

  • HTML 100
  • Schema 85.7
  • AIPM 71.4

Retrieval

Can this layer surface shared facts (location, contact, hours, pricing, FAQ, CTA)?

  • HTML 44.4
  • Schema 77.8
  • AIPM 77.8

Evidence

Answer quality vs independent gold (score strength). Partial credit counts; UNKNOWN scores zero unless gold is UNKNOWN.

  • HTML 60.5
  • Schema 62.7
  • AIPM 64.7

Metadata

Language, page kind, and freshness from page signals.

  • HTML 100
  • Schema 33.3
  • AIPM 66.7

Compression

Information delivered per token and context size. Higher means more matched answers for less context cost.

  • HTML 70.5
  • Schema 100
  • AIPM 99.5

Coverage map

AIPM matched 14 question(s); HTML matched 14. HTML/Schema (or a gap) still needed on Q5, Q8, Q15, Q16, Q18, Q19. No layer matched gold on Q15, Q16, Q18. Read this as complementary coverage — AIPM orients agents cheaply; HTML supplies depth when the sidecar cannot. HTML 14/20 matched (≈824 tok/match). Schema 14/20 matched (≈581 tok/match). AIPM 14/20 matched (≈584 tok/match). Figures are descriptive per layer — not a ranking. See per-question chains for sufficient layers, slice size, and measured cost.

AIPM matched

Q1, Q2, Q3, Q4, Q6, Q7, Q9, Q10, Q11, Q12, Q13, Q14, Q17, Q20

Alone: —

AIPM insufficient

Q5, Q8, Q15, Q16, Q18, Q19

HTML/Schema needed or all layers missed

Unanswered by all

Q15, Q16, Q18

HTML layer

Visible page text after stripping AIPM sidecars and JSON-LD. Measures what prose alone can answer.

Context fed: 22,915 chars

Tokens: 11,540 · median 1,525 ms

Matched this pack: 14/20

Stronger on

Understanding (100) · Metadata (100) · Compression (70.5) · Answer Efficiency (70.5)

Weaker on

—

Schema layer

JSON-LD structured data with minimal page chrome. Measures what schema markup can answer.

Context fed: 11,086 chars

Tokens: 8,135 · median 1,325 ms

Matched this pack: 14/20

Stronger on

Understanding (85.7) · Retrieval (77.8) · Compression (100) · Answer Efficiency (100)

Weaker on

Metadata (33.3)

AIPM layer

AI Page Manifest (.ai.json) only. Measures what the machine layer can answer without HTML.

Context fed: 13,294 chars

Tokens: 8,175 · median 1,295 ms

Matched this pack: 14/20

Stronger on

Understanding (71.4) · Retrieval (77.8) · Compression (99.5) · Answer Efficiency (99.5)

Weaker on

—

When to use which layer

AIPM complements HTML — it does not replace full-page prose.

Scenario Recommended Why
Fast orientation (title, purpose, brand, intent) Compare machine card → HTML fallback on this run Machine-card pack: 8,175 tok · $0.00134. Routing sim saved ~28% tokens vs HTML-always.
Deep content / research (prose facts, process detail) HTML (with optional machine orientation) HTML pack: 11,540 tok · $0.00194. Use when depth needs body prose.
Structured entity pulls (org, location, typed fields) Schema.org Schema pack: 8,135 tok · $0.00134. Dense JSON-LD tends to score well here.

Findings

  • —Of 20 questions: lowest measured retrieval cost among sufficient layers — HTML 4 · Schema 8 · AIPM 5 · multi-layer 0 · unanswered 3. Descriptive counts only; no overall ranking.
  • —Semantic Redundancy 66% — the manifest repeats the same ideas across fields. This inflates structural size without helping per-question retrieval.
  • —Manifest design: Merge or differentiate `purpose` and `abstract` (100% overlap).
  • —Structural size is secondary. A larger AIPM is not a failure if per-question retrieval stays tiny — check Semantic Redundancy instead.
  • —AIPM matched 14 question(s); HTML matched 14. HTML/Schema (or a gap) still needed on Q5, Q8, Q15, Q16, Q18, Q19. No layer matched gold on Q15, Q16, Q18. Read this as complementary coverage — AIPM orients agents cheaply; HTML supplies depth when the sidecar cannot. HTML 14/20 matched (≈824 tok/match). Schema 14/20 matched (≈581 tok/match). AIPM 14/20 matched (≈584 tok/match). Figures are descriptive per layer — not a ranking. See per-question chains for sufficient layers, slice size, and measured cost.

Question-by-question layer analysis

Which layer(s) could answer; which need more or different context; minimum context fed this run.

Q1 · Understanding · orientation

What is this page or business?

Gold: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026

Gold source: html.h1|title|jsonld.name · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 437 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML title+h1+meta_description+lead_paragraphs+prose_span+body_excerpt 594 api 2 medium yes
Schema name+headline+description 481 api 2 medium yes
AIPM title+primaryTopic+purpose+abstract+publisher+keyFacts+audience+contentIntent 437 api 2 medium yes
Execution chain · AIPM · 2 round(s)
  1. Question: What is this page or business?
  2. Planner: Planner mapped question `entity_what` on AIPM to minimal fields: title, primaryTopic.
  3. Slice: title+primaryTopic+purpose+abstract+publisher+keyFacts+audience+contentIntent — AIPM.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar AIPM.primaryTopic: AI visib...
  4. Actual input tokens: 437
  5. LLM answer: This page is about publishing llms.txt and llms-full.txt on WordPress with AigeoRadar for AI visibility.
  6. Evidence: AIPM.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar AIPM.primaryTopic: AI visibility AIPM.purpose: Publish llms.txt an...
  7. Confidence: medium · matched yes

Round 1: 124 in-tok · score 0 · miss

Round 2: 313 in-tok · score 63 · match

Execution chain · HTML · 2 round(s)
  1. Question: What is this page or business?
  2. Planner: Planner mapped question `entity_what` on HTML to minimal fields: title, h1.
  3. Slice: title+h1+meta_description+lead_paragraphs+prose_span+body_excerpt — HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar — AigeoRadar HTML.h1: WordP...
  4. Actual input tokens: 594
  5. LLM answer: This page is about AigeoRadar, which offers tools for publishing llms.txt and llms-full.txt on WordPress for Generative Engine Optimization (GEO).
  6. Evidence: HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar — AigeoRadar HTML.h1: WordPress GEO: llms.txt, llms-full.txt, and A...
  7. Confidence: medium · matched yes

Round 1: 143 in-tok · score 0 · miss

Round 2: 451 in-tok · score 58 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What is this page or business?
  2. Planner: Planner mapped question `entity_what` on SCHEMA to minimal fields: name, headline, description.
  3. Slice: name+headline+description — SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRada...
  4. Actual input tokens: 481
  5. LLM answer: This page is about AigeoRadar, which offers a one-click GEO deploy for publishing llms.txt and llms-full.txt on WordPress for visibility with ChatGPT, Perplexit...
  6. Evidence: SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar SCHEMA.description: Publish llms.txt...
  7. Confidence: medium · matched yes

Round 1: 162 in-tok · score 58 · match

Round 2: 319 in-tok · score 24 · miss

HTML

sufficient

This page is about AigeoRadar, which offers tools for publishing llms.txt and llms-full.txt on WordPress for Generative Engine Optimization (GEO).

score 58 · 22,915 chars context · 594 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

This page is about AigeoRadar, which offers a one-click GEO deploy for publishing llms.txt and llms-full.txt on WordPress for visibility with ChatGPT, Perplexity, and Gemini.

score 58 · 11,086 chars context · 481 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

This page is about publishing llms.txt and llms-full.txt on WordPress with AigeoRadar for AI visibility.

score 63 · 13,294 chars context · 437 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q2 · Understanding · orientation

What is the main service or product offered?

Gold: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026

Gold source: html.h1|meta|prose · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 481 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML h1+title+meta_description+lead_paragraphs+prose_span+body_excerpt 598 api 2 medium yes
Schema name+headline+description 485 api 2 medium yes
AIPM primaryTopic+title+purpose+abstract+publisher+keyFacts+audience+contentIntent 481 api 2 medium yes
Execution chain · AIPM · 2 round(s)
  1. Question: What is the main service or product offered?
  2. Planner: Planner mapped question `main_service` on AIPM to minimal fields: primaryTopic, title, purpose.
  3. Slice: primaryTopic+title+purpose+abstract+publisher+keyFacts+audience+contentIntent — AIPM.primaryTopic: AI visibility AIPM.title: WordPress GEO: llms.txt and AI Discovery Guide | Aigeo...
  4. Actual input tokens: 481
  5. LLM answer: The main service offered is the publication of llms.txt and llms-full.txt on WordPress for AI visibility.
  6. Evidence: AIPM.primaryTopic: AI visibility AIPM.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar AIPM.purpose: Publish llms.txt an...
  7. Confidence: medium · matched yes

Round 1: 166 in-tok · score 58 · match

Round 2: 315 in-tok · score 59 · match

Execution chain · HTML · 2 round(s)
  1. Question: What is the main service or product offered?
  2. Planner: Planner mapped question `main_service` on HTML to minimal fields: h1, title.
  3. Slice: h1+title+meta_description+lead_paragraphs+prose_span+body_excerpt — HTML.h1: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026 HTML.title: WordPress GEO...
  4. Actual input tokens: 598
  5. LLM answer: The main service offered is the ability to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for Generative Engine Optimization (GEO).
  6. Evidence: HTML.h1: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026 HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | Aige...
  7. Confidence: medium · matched yes

Round 1: 145 in-tok · score 0 · miss

Round 2: 453 in-tok · score 58 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What is the main service or product offered?
  2. Planner: Planner mapped question `main_service` on SCHEMA to minimal fields: name, headline, description.
  3. Slice: name+headline+description — SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRada...
  4. Actual input tokens: 485
  5. LLM answer: The main service offered is publishing llms.txt and llms-full.txt on WordPress with AigeoRadar.
  6. Evidence: SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar SCHEMA.description: Publish llms.txt...
  7. Confidence: medium · matched yes

Round 1: 164 in-tok · score 50 · match

Round 2: 321 in-tok · score 23 · miss

HTML

sufficient

The main service offered is the ability to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for Generative Engine Optimization (GEO).

score 58 · 22,915 chars context · 598 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

The main service offered is publishing llms.txt and llms-full.txt on WordPress with AigeoRadar.

score 50 · 11,086 chars context · 485 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

The main service offered is the publication of llms.txt and llms-full.txt on WordPress for AI visibility.

score 59 · 13,294 chars context · 481 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q3 · Understanding · orientation

Who is the publisher or brand?

Gold: AigeoRadar

Gold source: html.jsonld|title · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 103 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML title 118 api 1 high yes
Schema publisher+name 111 api 1 high yes
AIPM publisher 103 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on AIPM to minimal fields: publisher.
  3. Slice: publisher — AIPM.publisher: AigeoRadar
  4. Actual input tokens: 103
  5. LLM answer: AigeoRadar.
  6. Evidence: AIPM.publisher: AigeoRadar
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on HTML to minimal fields: title.
  3. Slice: title — HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar — AigeoRadar
  4. Actual input tokens: 118
  5. LLM answer: AigeoRadar.
  6. Evidence: HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar — AigeoRadar
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: Who is the publisher or brand?
  2. Planner: Planner mapped question `publisher` on SCHEMA to minimal fields: publisher, name.
  3. Slice: publisher+name — SCHEMA.publisher: AigeoRadar SCHEMA.name: AigeoRadar
  4. Actual input tokens: 111
  5. LLM answer: AigeoRadar.
  6. Evidence: SCHEMA.publisher: AigeoRadar SCHEMA.name: AigeoRadar
  7. Confidence: high · matched yes

HTML

sufficient

AigeoRadar.

score 100 · 22,915 chars context · 118 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

AigeoRadar.

score 100 · 11,086 chars context · 111 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

AigeoRadar.

score 100 · 13,294 chars context · 103 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q4 · Retrieval · depth

Where does this business operate or which city is mentioned?

Gold: UNKNOWN

Gold source: html.address|prose|jsonld · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 284 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span+lead_paragraphs+title+h1+meta_description+body_excerpt 621 api 2 low yes
Schema name+headline+description+publisher+@type+block 284 api 2 low yes
AIPM purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent 317 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: Where does this business operate or which city is mentioned?
  2. Planner: Planner mapped question `geo_signal` on AIPM to minimal fields: geo, areaServed, address.
  3. Slice: purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent — AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 317
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 0 in-tok · score 0 · miss

Round 2: 317 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: Where does this business operate or which city is mentioned?
  2. Planner: Planner mapped question `geo_signal` on HTML to minimal fields: prose_span, lead_paragraphs.
  3. Slice: prose_span+lead_paragraphs+title+h1+meta_description+body_excerpt — HTML.prose_span: UNKNOWN HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with...
  4. Actual input tokens: 621
  5. LLM answer: UNKNOWN
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 185 in-tok · score 100 · match

Round 2: 436 in-tok · score 100 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: Where does this business operate or which city is mentioned?
  2. Planner: Planner mapped question `geo_signal` on SCHEMA to minimal fields: address, addressLocality, areaServed.
  3. Slice: name+headline+description+publisher+@type+block — SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRada...
  4. Actual input tokens: 284
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 0 in-tok · score 0 · miss

Round 2: 284 in-tok · score 100 · match

HTML

sufficient

UNKNOWN

score 100 · 22,915 chars context · 621 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 284 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 317 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q5 · Understanding · orientation

Who is the intended audience of this page?

Gold: businesses

Gold source: html.prose|meta · html_independent

Sufficient: HTML · Needs more / other context: Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 214 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs 214 api 1 high yes
Schema description+name+headline+publisher+@type+block 463 api 2 low no
AIPM audience+purpose+abstract+primaryTopic+title+publisher+keyFacts+contentIntent 466 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: Who is the intended audience of this page?
  2. Planner: Planner mapped question `audience` on AIPM to minimal fields: audience, purpose.
  3. Slice: audience+purpose+abstract+primaryTopic+title+publisher+keyFacts+contentIntent — AIPM.audience: ["B2B","agency","SMB"] AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress...
  4. Actual input tokens: 466
  5. LLM answer: The intended audience of this page includes B2B, agency, and SMB.
  6. Evidence: AIPM.audience: ["B2B","agency","SMB"] AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy f...
  7. Confidence: low · matched no

Round 1: 151 in-tok · score 0 · miss

Round 2: 315 in-tok · score 0 · miss

Execution chain · HTML · 1 round(s)
  1. Question: Who is the intended audience of this page?
  2. Planner: Planner mapped question `audience` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs — HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GE...
  4. Actual input tokens: 214
  5. LLM answer: The intended audience of this page is individuals or businesses running a WordPress site.
  6. Evidence: HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Ge...
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: Who is the intended audience of this page?
  2. Planner: Planner mapped question `audience` on SCHEMA to minimal fields: description, name.
  3. Slice: description+name+headline+publisher+@type+block — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 463
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 142 in-tok · score 0 · miss

Round 2: 321 in-tok · score 0 · miss

Root cause · Layer miss

Improve orientation fields; do not paste full HTML into the sidecar.

HTML

sufficient

The intended audience of this page is individuals or businesses running a WordPress site.

score 88 · 22,915 chars context · 214 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 463 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

insufficient

The intended audience of this page includes B2B, agency, and SMB.

score 0 · 13,294 chars context · 466 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q6 · Understanding · orientation

What is the purpose of this page?

Gold: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemini visibility.

Gold source: html.page_summary · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost AIPM · 134 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt 678 api 2 low yes
Schema description+name 141 api 1 high yes
AIPM purpose 134 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on AIPM to minimal fields: purpose.
  3. Slice: purpose — AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 134
  5. LLM answer: The purpose of this page is to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for one-click GEO deploy for ChatGPT, Perplexity, and Gemini visi...
  6. Evidence: AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemini visi...
  7. Confidence: high · matched yes
Execution chain · HTML · 2 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt — HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GE...
  4. Actual input tokens: 678
  5. LLM answer: The purpose of this page is to promote the publishing of llms.txt and llms-full.txt on WordPress using AigeoRadar for improved AI visibility and discovery.
  6. Evidence: HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Ge...
  7. Confidence: low · matched yes

Round 1: 213 in-tok · score 46 · match

Round 2: 465 in-tok · score 46 · match

Execution chain · SCHEMA · 1 round(s)
  1. Question: What is the purpose of this page?
  2. Planner: Planner mapped question `purpose` on SCHEMA to minimal fields: description, name.
  3. Slice: description+name — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 141
  5. LLM answer: The purpose of this page is to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for one-click GEO deployment for ChatGPT, Perplexity, and Gemini...
  6. Evidence: SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemin...
  7. Confidence: high · matched yes

HTML

sufficient

The purpose of this page is to promote the publishing of llms.txt and llms-full.txt on WordPress using AigeoRadar for improved AI visibility and discovery.

score 46 · 22,915 chars context · 678 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

The purpose of this page is to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for one-click GEO deployment for ChatGPT, Perplexity, and Gemini visibility.

score 93 · 11,086 chars context · 141 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

The purpose of this page is to publish llms.txt and llms-full.txt on WordPress with AigeoRadar for one-click GEO deploy for ChatGPT, Perplexity, and Gemini visibility.

score 100 · 13,294 chars context · 134 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q7 · Understanding · orientation

Summarize this page in one sentence.

Gold: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemini visibility.

Gold source: html.page_summary · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 142 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs 214 api 1 medium yes
Schema description+name 142 api 1 high yes
AIPM abstract+purpose 174 api 1 medium yes
Execution chain · AIPM · 1 round(s)
  1. Question: Summarize this page in one sentence.
  2. Planner: Planner mapped question `abstract` on AIPM to minimal fields: abstract, purpose.
  3. Slice: abstract+purpose — AIPM.abstract: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 174
  5. LLM answer: The page discusses publishing llms.txt and llms-full.txt on WordPress using AigeoRadar for easy deployment of visibility for ChatGPT, Perplexity, and Gemini.
  6. Evidence: AIPM.abstract: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemini vis...
  7. Confidence: medium · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: Summarize this page in one sentence.
  2. Planner: Planner mapped question `abstract` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs — HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GE...
  4. Actual input tokens: 214
  5. LLM answer: The page discusses publishing llms.txt and llms-full.txt on WordPress using AigeoRadar for improved visibility of AI assistants like ChatGPT, Perplexity, and Ge...
  6. Evidence: HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Ge...
  7. Confidence: medium · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: Summarize this page in one sentence.
  2. Planner: Planner mapped question `abstract` on SCHEMA to minimal fields: description, name.
  3. Slice: description+name — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 142
  5. LLM answer: AigeoRadar allows for the publishing of llms.txt and llms-full.txt on WordPress with a one-click GEO deploy for ChatGPT, Perplexity, and Gemini visibility.
  6. Evidence: SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gemin...
  7. Confidence: high · matched yes

HTML

sufficient

The page discusses publishing llms.txt and llms-full.txt on WordPress using AigeoRadar for improved visibility of AI assistants like ChatGPT, Perplexity, and Gemini through one-click GEO deployment.

score 79 · 22,915 chars context · 214 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

AigeoRadar allows for the publishing of llms.txt and llms-full.txt on WordPress with a one-click GEO deploy for ChatGPT, Perplexity, and Gemini visibility.

score 90 · 11,086 chars context · 142 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

The page discusses publishing llms.txt and llms-full.txt on WordPress using AigeoRadar for easy deployment of visibility for ChatGPT, Perplexity, and Gemini.

score 64 · 13,294 chars context · 174 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q8 · Understanding · orientation

What is the primary topic or headline of this page?

Gold: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026

Gold source: html.h1|title · html_independent

Sufficient: HTML, Schema · Needs more / other context: AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 147 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML h1+title 147 api 1 high yes
Schema name+headline+description 166 api 1 medium yes
AIPM primaryTopic+title+purpose+abstract+publisher+keyFacts+audience+contentIntent 485 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What is the primary topic or headline of this page?
  2. Planner: Planner mapped question `primary_topic` on AIPM to minimal fields: primaryTopic, title, purpose.
  3. Slice: primaryTopic+title+purpose+abstract+publisher+keyFacts+audience+contentIntent — AIPM.primaryTopic: AI visibility AIPM.title: WordPress GEO: llms.txt and AI Discovery Guide | Aigeo...
  4. Actual input tokens: 485
  5. LLM answer: AI visibility
  6. Evidence: AI visibility
  7. Confidence: low · matched no

Round 1: 168 in-tok · score 20 · miss

Round 2: 317 in-tok · score 20 · miss

Execution chain · HTML · 1 round(s)
  1. Question: What is the primary topic or headline of this page?
  2. Planner: Planner mapped question `primary_topic` on HTML to minimal fields: h1, title.
  3. Slice: h1+title — HTML.h1: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026 HTML.title: WordPress GEO...
  4. Actual input tokens: 147
  5. LLM answer: The primary topic or headline of this page is "WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026."
  6. Evidence: HTML.h1: WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026 HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | Aige...
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: What is the primary topic or headline of this page?
  2. Planner: Planner mapped question `primary_topic` on SCHEMA to minimal fields: name, headline, description.
  3. Slice: name+headline+description — SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRada...
  4. Actual input tokens: 166
  5. LLM answer: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar.
  6. Evidence: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar
  7. Confidence: medium · matched yes

Root cause · Layer miss

Improve orientation fields; do not paste full HTML into the sidecar.

HTML

sufficient

The primary topic or headline of this page is "WordPress GEO: llms.txt, llms-full.txt, and AI discovery in 2026."

score 87 · 22,915 chars context · 147 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar.

score 75 · 11,086 chars context · 166 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

insufficient

AI visibility

score 20 · 13,294 chars context · 485 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q9 · Metadata · orientation

What language is this page written in?

Gold: en

Gold source: html.lang · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 100 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lang 100 api 1 high yes
Schema inLanguage 101 api 1 high yes
AIPM inLanguage 102 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What language is this page written in?
  2. Planner: Planner mapped question `language` on AIPM to minimal fields: inLanguage.
  3. Slice: inLanguage — AIPM.inLanguage: en
  4. Actual input tokens: 102
  5. LLM answer: The page is written in English.
  6. Evidence: AIPM.inLanguage: en
  7. Confidence: high · matched yes
Execution chain · HTML · 1 round(s)
  1. Question: What language is this page written in?
  2. Planner: Planner mapped question `language` on HTML to minimal fields: lang.
  3. Slice: lang — HTML.lang: lang=en
  4. Actual input tokens: 100
  5. LLM answer: The page is written in English.
  6. Evidence: HTML.lang: lang=en
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 1 round(s)
  1. Question: What language is this page written in?
  2. Planner: Planner mapped question `language` on SCHEMA to minimal fields: inLanguage.
  3. Slice: inLanguage — SCHEMA.inLanguage: en
  4. Actual input tokens: 101
  5. LLM answer: The page is written in English.
  6. Evidence: SCHEMA.inLanguage: en
  7. Confidence: high · matched yes

HTML

sufficient

The page is written in English.

score 88 · 22,915 chars context · 100 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

The page is written in English.

score 88 · 11,086 chars context · 101 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

The page is written in English.

score 88 · 13,294 chars context · 102 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q10 · Retrieval · depth

What phone number or contact detail is listed?

Gold: UNKNOWN

Gold source: html.title|prose|jsonld.telephone · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 517 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML title+lead_paragraphs+h1+meta_description+prose_span+body_excerpt 635 api 2 low yes
Schema block+description+name+headline+publisher+@type 517 api 2 low yes
AIPM keyFacts+publisher+abstract+purpose+primaryTopic+title+audience+contentIntent 534 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: What phone number or contact detail is listed?
  2. Planner: Planner mapped question `contact_phone` on AIPM to minimal fields: keyFacts, publisher, abstract.
  3. Slice: keyFacts+publisher+abstract+purpose+primaryTopic+title+audience+contentIntent — AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization) is the next layer a...
  4. Actual input tokens: 534
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 219 in-tok · score 100 · match

Round 2: 315 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: What phone number or contact detail is listed?
  2. Planner: Planner mapped question `contact_phone` on HTML to minimal fields: title, lead_paragraphs.
  3. Slice: title+lead_paragraphs+h1+meta_description+prose_span+body_excerpt — HTML.title: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRadar — AigeoRadar HTML.lead_para...
  4. Actual input tokens: 635
  5. LLM answer: UNKNOWN
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 201 in-tok · score 100 · match

Round 2: 434 in-tok · score 100 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What phone number or contact detail is listed?
  2. Planner: Planner mapped question `contact_phone` on SCHEMA to minimal fields: telephone, block, description.
  3. Slice: block+description+name+headline+publisher+@type — SCHEMA.block: { "@context": "https://schema.org", "@graph": [ { "@type":...
  4. Actual input tokens: 517
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 235 in-tok · score 100 · match

Round 2: 282 in-tok · score 100 · match

HTML

sufficient

UNKNOWN

score 100 · 22,915 chars context · 635 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 517 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 534 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q11 · Retrieval · depth

What physical address is listed for this business?

Gold: UNKNOWN

Gold source: html.prose|jsonld.address · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 282 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML prose_span+lead_paragraphs+title+h1+meta_description+body_excerpt 617 api 2 low yes
Schema name+headline+description+publisher+@type+block 282 api 2 low yes
AIPM purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent 315 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: What physical address is listed for this business?
  2. Planner: Planner mapped question `address` on AIPM to minimal fields: address, geo, areaServed.
  3. Slice: purpose+abstract+primaryTopic+title+publisher+keyFacts+audience+contentIntent — AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 315
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 0 in-tok · score 0 · miss

Round 2: 315 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: What physical address is listed for this business?
  2. Planner: Planner mapped question `address` on HTML to minimal fields: prose_span, lead_paragraphs.
  3. Slice: prose_span+lead_paragraphs+title+h1+meta_description+body_excerpt — HTML.prose_span: UNKNOWN HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with...
  4. Actual input tokens: 617
  5. LLM answer: UNKNOWN
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 183 in-tok · score 100 · match

Round 2: 434 in-tok · score 100 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What physical address is listed for this business?
  2. Planner: Planner mapped question `address` on SCHEMA to minimal fields: address, addressLocality, areaServed.
  3. Slice: name+headline+description+publisher+@type+block — SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI Discovery Guide | AigeoRada...
  4. Actual input tokens: 282
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 0 in-tok · score 0 · miss

Round 2: 282 in-tok · score 100 · match

HTML

sufficient

UNKNOWN

score 100 · 22,915 chars context · 617 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 282 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 315 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q12 · Retrieval · depth

What are the opening hours or availability?

Gold: UNKNOWN

Gold source: html.prose|jsonld.openingHours · html_independent

Sufficient: HTML, Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 515 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 778 api 2 low yes
Schema block+description+name+headline+publisher+@type 515 api 2 low yes
AIPM keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent 562 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: What are the opening hours or availability?
  2. Planner: Planner mapped question `hours` on AIPM to minimal fields: keyFacts, abstract, purpose.
  3. Slice: keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization) is the next layer a...
  4. Actual input tokens: 562
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 248 in-tok · score 100 · match

Round 2: 314 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: What are the opening hours or availability?
  2. Planner: Planner mapped question `hours` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 778
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 345 in-tok · score 100 · match

Round 2: 433 in-tok · score 100 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What are the opening hours or availability?
  2. Planner: Planner mapped question `hours` on SCHEMA to minimal fields: openingHours, block, description.
  3. Slice: block+description+name+headline+publisher+@type — SCHEMA.block: { "@context": "https://schema.org", "@graph": [ { "@type":...
  4. Actual input tokens: 515
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 234 in-tok · score 100 · match

Round 2: 281 in-tok · score 100 · match

HTML

sufficient

UNKNOWN.

score 100 · 22,915 chars context · 778 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 515 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 562 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q13 · Retrieval · depth

Is pricing or package information mentioned, and what is it?

Gold: UNKNOWN

Gold source: html.prose|jsonld.offers · html_independent

Sufficient: Schema, AIPM · Needs more / other context: HTML

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 523 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 786 api 2 low no
Schema block+description+name+headline+publisher+@type 523 api 2 low yes
AIPM keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent 530 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: Is pricing or package information mentioned, and what is it?
  2. Planner: Planner mapped question `pricing` on AIPM to minimal fields: keyFacts, sections, abstract.
  3. Slice: keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization) is the next layer a...
  4. Actual input tokens: 530
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 212 in-tok · score 100 · match

Round 2: 318 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: Is pricing or package information mentioned, and what is it?
  2. Planner: Planner mapped question `pricing` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 786
  5. LLM answer: Yes, the starter plan is $9.90 per month and includes one WordPress site with plugin sync.
  6. Evidence: HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gem...
  7. Confidence: low · matched no

Round 1: 349 in-tok · score 0 · miss

Round 2: 437 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: Is pricing or package information mentioned, and what is it?
  2. Planner: Planner mapped question `pricing` on SCHEMA to minimal fields: offers, price, block, description.
  3. Slice: block+description+name+headline+publisher+@type — SCHEMA.block: { "@context": "https://schema.org", "@graph": [ { "@type":...
  4. Actual input tokens: 523
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 238 in-tok · score 100 · match

Round 2: 285 in-tok · score 100 · match

HTML

insufficient

Yes, the starter plan is $9.90 per month and includes one WordPress site with plugin sync.

score 0 · 22,915 chars context · 786 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 523 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 530 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q14 · Retrieval · depth

What makes this offer different or stand out?

Gold: UNKNOWN

Gold source: html.prose|meta · html_independent

Sufficient: Schema, AIPM · Needs more / other context: HTML

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 526 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 780 api 2 low no
Schema description+block+name+headline+publisher+@type 526 api 2 low yes
AIPM keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent 564 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: What makes this offer different or stand out?
  2. Planner: Planner mapped question `differentiator` on AIPM to minimal fields: keyFacts, abstract, purpose.
  3. Slice: keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization) is the next layer a...
  4. Actual input tokens: 564
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 249 in-tok · score 100 · match

Round 2: 315 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: What makes this offer different or stand out?
  2. Planner: Planner mapped question `differentiator` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 780
  5. LLM answer: The offer stands out by providing a one-click GEO deploy for AI visibility on platforms like ChatGPT, Perplexity, and Gemini, specifically tailored for WordPres...
  6. Evidence: HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gem...
  7. Confidence: low · matched no

Round 1: 346 in-tok · score 0 · miss

Round 2: 434 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What makes this offer different or stand out?
  2. Planner: Planner mapped question `differentiator` on SCHEMA to minimal fields: description, block, name.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 526
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 244 in-tok · score 100 · match

Round 2: 282 in-tok · score 100 · match

HTML

insufficient

The offer stands out by providing a one-click GEO deploy for AI visibility on platforms like ChatGPT, Perplexity, and Gemini, specifically tailored for WordPress sites.

score 0 · 22,915 chars context · 780 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 526 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 564 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q15 · Evidence · depth

What trust signals are present (reviews, certificates, guarantees, years of experience)?

Gold: review

Gold source: html.prose|jsonld · html_independent

No layer provided a sufficient answer from its context alone.

Measured retrieval cost (API tokens) · lowest cost AIPM · 480 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 794 api 2 low no
Schema description+block+name+headline+publisher+@type 540 api 2 low no
AIPM keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent 480 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What trust signals are present (reviews, certificates, guarantees, years of experience)?
  2. Planner: Planner mapped question `trust` on AIPM to minimal fields: keyFacts, abstract, purpose.
  3. Slice: keyFacts+abstract+purpose+primaryTopic+title+publisher+audience+contentIntent — AIPM.keyFacts: Start with the free scan Enter your domain on aigeoradar.com for an instant AI visibi...
  4. Actual input tokens: 480
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 207 in-tok · score 0 · miss

Round 2: 273 in-tok · score 0 · miss

Execution chain · HTML · 2 round(s)
  1. Question: What trust signals are present (reviews, certificates, guarantees, years of experience)?
  2. Planner: Planner mapped question `trust` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 794
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 353 in-tok · score 0 · miss

Round 2: 441 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What trust signals are present (reviews, certificates, guarantees, years of experience)?
  2. Planner: Planner mapped question `trust` on SCHEMA to minimal fields: description, block, name.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 540
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 251 in-tok · score 0 · miss

Round 2: 289 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

insufficient

UNKNOWN.

score 0 · 22,915 chars context · 794 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 540 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 13,294 chars context · 480 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q16 · Retrieval · depth

What frequently asked questions or FAQ topics are covered?

Gold: FAQ topics are present on the page

Gold source: html.faq|jsonld.FAQPage · html_independent

No layer provided a sufficient answer from its context alone.

Measured retrieval cost (API tokens) · lowest cost AIPM · 503 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 794 api 2 low no
Schema block+description+name+headline+publisher+@type 519 api 2 low no
AIPM faqEntity+keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent 503 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What frequently asked questions or FAQ topics are covered?
  2. Planner: Planner mapped question `faq` on AIPM to minimal fields: faqEntity, keyFacts.
  3. Slice: faqEntity+keyFacts+purpose+abstract+primaryTopic+title+publisher+audience+contentIntent — AIPM.faqEntity: [] AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization)...
  4. Actual input tokens: 503
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 179 in-tok · score 0 · miss

Round 2: 324 in-tok · score 0 · miss

Execution chain · HTML · 2 round(s)
  1. Question: What frequently asked questions or FAQ topics are covered?
  2. Planner: Planner mapped question `faq` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 794
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 353 in-tok · score 0 · miss

Round 2: 441 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What frequently asked questions or FAQ topics are covered?
  2. Planner: Planner mapped question `faq` on SCHEMA to minimal fields: block, description.
  3. Slice: block+description+name+headline+publisher+@type — SCHEMA.block: { "@context": "https://schema.org", "@graph": [ { "@type":...
  4. Actual input tokens: 519
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 236 in-tok · score 0 · miss

Round 2: 283 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

insufficient

UNKNOWN.

score 0 · 22,915 chars context · 794 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 519 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 13,294 chars context · 503 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q17 · Retrieval · depth

What action should the visitor take (call, buy, contact, book)?

Gold: UNKNOWN

Gold source: html.cta|prose · html_independent

Sufficient: Schema, AIPM · Needs more / other context: HTML

Measured retrieval cost (API tokens) · lowest cost SCHEMA · 538 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description 792 api 2 low no
Schema description+block+name+headline+publisher+@type 538 api 2 low yes
AIPM purpose+abstract+keyFacts+primaryTopic+title+publisher+audience+contentIntent 576 api 2 low yes
Execution chain · AIPM · 2 round(s)
  1. Question: What action should the visitor take (call, buy, contact, book)?
  2. Planner: Planner mapped question `cta` on AIPM to minimal fields: purpose, abstract, keyFacts.
  3. Slice: purpose+abstract+keyFacts+primaryTopic+title+publisher+audience+contentIntent — AIPM.purpose: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 576
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 255 in-tok · score 100 · match

Round 2: 321 in-tok · score 100 · match

Execution chain · HTML · 2 round(s)
  1. Question: What action should the visitor take (call, buy, contact, book)?
  2. Planner: Planner mapped question `cta` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span+title+h1+meta_description — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 792
  5. LLM answer: Enter your domain on aigeoradar.com for an instant AI visibility preview.
  6. Evidence: Enter your domain on aigeoradar.com for an instant AI visibility preview. No credit card required.
  7. Confidence: low · matched no

Round 1: 352 in-tok · score 0 · miss

Round 2: 440 in-tok · score 0 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What action should the visitor take (call, buy, contact, book)?
  2. Planner: Planner mapped question `cta` on SCHEMA to minimal fields: description, block, name.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 538
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched yes

Round 1: 250 in-tok · score 100 · match

Round 2: 288 in-tok · score 100 · match

HTML

insufficient

Enter your domain on aigeoradar.com for an instant AI visibility preview.

score 0 · 22,915 chars context · 792 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

sufficient

UNKNOWN.

score 100 · 11,086 chars context · 538 in-tokens

Schema answered using 11086 chars of layer context (minimum fed this run).

AIPM

sufficient

UNKNOWN.

score 100 · 13,294 chars context · 576 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Q18 · Retrieval · depth

What related products, services, or pages are mentioned?

Gold: Features, What is AigeoRadar?, Pricing

Gold source: html.nav|prose · html_independent

No layer provided a sufficient answer from its context alone.

Measured retrieval cost (API tokens) · lowest cost AIPM · 498 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span 802 api 2 low no
Schema description+block+name+headline+publisher+@type 530 api 2 low no
AIPM keyFacts+primaryTopic+purpose+abstract+title+publisher+audience+contentIntent 498 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: What related products, services, or pages are mentioned?
  2. Planner: Planner mapped question `related` on AIPM to minimal fields: sections, keyFacts, primaryTopic.
  3. Slice: keyFacts+primaryTopic+purpose+abstract+title+publisher+audience+contentIntent — AIPM.keyFacts: If you run a WordPress site, GEO (Generative Engine Optimization) is the next layer a...
  4. Actual input tokens: 498
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 181 in-tok · score 0 · miss

Round 2: 317 in-tok · score 0 · miss

Execution chain · HTML · 2 round(s)
  1. Question: What related products, services, or pages are mentioned?
  2. Planner: Planner mapped question `related` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 802
  5. LLM answer: AigeoRadar, WordPress plugin, Shopify app for GEO discovery deploy.
  6. Evidence: HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gem...
  7. Confidence: low · matched no

Round 1: 357 in-tok · score 18 · miss

Round 2: 445 in-tok · score 17 · miss

Execution chain · SCHEMA · 2 round(s)
  1. Question: What related products, services, or pages are mentioned?
  2. Planner: Planner mapped question `related` on SCHEMA to minimal fields: description, block, name.
  3. Slice: description+block+name+headline+publisher+@type — SCHEMA.description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO d...
  4. Actual input tokens: 530
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 246 in-tok · score 0 · miss

Round 2: 284 in-tok · score 0 · miss

Root cause · Depth gap (expected)

Prose/detail questions belong to HTML — escalate after AIPM orientation.

HTML

insufficient

AigeoRadar, WordPress plugin, Shopify app for GEO discovery deploy.

score 18 · 22,915 chars context · 802 in-tokens

HTML did not answer from 22915 chars of context — additional or different layer context needed.

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 530 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 13,294 chars context · 498 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q19 · Metadata · orientation

When was this page published or last updated?

Gold: 2026-07-29

Gold source: html.time|jsonld.dateModified · html_independent

Sufficient: HTML · Needs more / other context: Schema, AIPM

Measured retrieval cost (API tokens) · lowest cost HTML · 351 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML lead_paragraphs+body_excerpt+prose_span 351 api 1 high yes
Schema block+description+name+headline+publisher+@type 595 api 2 low no
AIPM abstract+keyFacts+title+purpose+primaryTopic+publisher+audience+contentIntent 546 api 2 low no
Execution chain · AIPM · 2 round(s)
  1. Question: When was this page published or last updated?
  2. Planner: Planner mapped question `freshness` on AIPM to minimal fields: abstract, keyFacts, title.
  3. Slice: abstract+keyFacts+title+purpose+primaryTopic+publisher+audience+contentIntent — AIPM.abstract: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy...
  4. Actual input tokens: 546
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 231 in-tok · score 0 · miss

Round 2: 315 in-tok · score 0 · miss

Execution chain · HTML · 1 round(s)
  1. Question: When was this page published or last updated?
  2. Planner: Planner mapped question `freshness` on HTML to minimal fields: lead_paragraphs, body_excerpt, prose_span.
  3. Slice: lead_paragraphs+body_excerpt+prose_span — HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO...
  4. Actual input tokens: 351
  5. LLM answer: The page was published or last updated on 2026-07-29.
  6. Evidence: HTML.lead_paragraphs: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GEO deploy for ChatGPT, Perplexity, and Gem...
  7. Confidence: high · matched yes
Execution chain · SCHEMA · 2 round(s)
  1. Question: When was this page published or last updated?
  2. Planner: Planner mapped question `freshness` on SCHEMA to minimal fields: block, description.
  3. Slice: block+description+name+headline+publisher+@type — SCHEMA.block: { "@context": "https://schema.org", "@graph": [ { "@type":...
  4. Actual input tokens: 595
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 274 in-tok · score 0 · miss

Round 2: 321 in-tok · score 0 · miss

Root cause · Missing in manifest

Add or fix the corresponding AIPM field (title, purpose, primaryTopic, publisher, inLanguage).

HTML

sufficient

The page was published or last updated on 2026-07-29.

score 88 · 22,915 chars context · 351 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 595 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

insufficient

UNKNOWN.

score 0 · 13,294 chars context · 546 in-tokens

AIPM did not answer from 13294 chars of context — additional or different layer context needed.

Q20 · Metadata · orientation

What kind of page is this (article, product, local service, company page, FAQ, other)?

Gold: product

Gold source: html.heuristic|jsonld.@type · html_independent

Sufficient: HTML, AIPM · Needs more / other context: Schema

Measured retrieval cost (API tokens) · lowest cost AIPM · 124 input tokens

Layer Planner fields Input tokens Rounds Confidence OK?
HTML meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt 672 api 2 high yes
Schema @type+name+headline+description+publisher+block 408 api 2 low no
AIPM contentIntent+pageType 124 api 1 high yes
Execution chain · AIPM · 1 round(s)
  1. Question: What kind of page is this (article, product, local service, company page, FAQ, other)?
  2. Planner: Planner mapped question `page_kind` on AIPM to minimal fields: contentIntent, pageType.
  3. Slice: contentIntent+pageType — AIPM.contentIntent: informational AIPM.pageType: blog
  4. Actual input tokens: 124
  5. LLM answer: blog
  6. Evidence: blog
  7. Confidence: high · matched yes
Execution chain · HTML · 2 round(s)
  1. Question: What kind of page is this (article, product, local service, company page, FAQ, other)?
  2. Planner: Planner mapped question `page_kind` on HTML to minimal fields: meta_description, lead_paragraphs.
  3. Slice: meta_description+lead_paragraphs+title+h1+prose_span+body_excerpt — HTML.meta_description: Publish llms.txt and llms-full.txt on WordPress with AigeoRadar. One-click GE...
  4. Actual input tokens: 672
  5. LLM answer: product
  6. Evidence: product
  7. Confidence: high · matched yes

Round 1: 226 in-tok · score 0 · miss

Round 2: 446 in-tok · score 100 · match

Execution chain · SCHEMA · 2 round(s)
  1. Question: What kind of page is this (article, product, local service, company page, FAQ, other)?
  2. Planner: Planner mapped question `page_kind` on SCHEMA to minimal fields: @type.
  3. Slice: @type+name+headline+description+publisher+block — SCHEMA.@type: Organization SCHEMA.name: AigeoRadar SCHEMA.headline: WordPress GEO: llms.txt and AI...
  4. Actual input tokens: 408
  5. LLM answer: UNKNOWN.
  6. Evidence: —
  7. Confidence: low · matched no

Round 1: 114 in-tok · score 0 · miss

Round 2: 294 in-tok · score 0 · miss

HTML

sufficient

product

score 100 · 22,915 chars context · 672 in-tokens

HTML answered using 22915 chars of layer context (minimum fed this run).

Schema

insufficient

UNKNOWN.

score 0 · 11,086 chars context · 408 in-tokens

Schema did not answer from 11086 chars of context — additional or different layer context needed.

AIPM

sufficient

blog

score 100 · 13,294 chars context · 124 in-tokens

AIPM answered using 13294 chars of layer context (minimum fed this run).

Methodology

  • AI Context Benchmark: Planner → Slice → LLM with measured API input tokens.
  • Reports describe sufficient layers, slice size, cost, and evidence — they do not declare a winning format.
  • Layers under test today: HTML, Schema.org, AIPM (extensible to RSS, Markdown, PDF, …).
  • Engine aipm_benchmark_v4 · Wed, Jul 29, 2026 11:33 PM · aipm_benchmark_score_v10

Share

Per-question context chain across layers.

Post on X LinkedIn WhatsApp
About the lab →