feat(seo/geo): split into parallel seo + geo agents with shared resources
Refactor the monolithic seo-analyzer into two specialist agents orchestrated in parallel by the /seo skill, plus a standalone /geo skill for AI-only audits. Changes - agents/seo-analyzer.md: refocused on classical engines (Google, Bing, DuckDuckGo). Adds Core Web Vitals 2.0 (LCP/INP/CLS + VSI), CSP + full security headers, hreflang audit, video SEO (transcripts), accessibility as ranking signal, image/video sitemaps. - agents/geo-analyzer.md: new agent for AI engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Copilot). Covers AI crawler policy, llms.txt/llms-full.txt, Schema.org for AI extraction (QAPage, Speakable, Person+Article, Organization graph), entity SEO (Wikidata, sameAs, Knowledge Panel), content shape (Definition Lead, TL;DR, Q->A, citable stats, freshness), AI visibility testing. - agents/resources/: shared knowledge base referenced by both agents — ai-crawlers-2026.md (25+ bots, training vs retrieval categories, permissive/restrictive templates), llms-txt-template.md, geo-schemas.md (incl. deprecated list: ClaimReview, CourseInfo, etc. removed June 2025), entity-seo.md, content-shape-for-ai.md, ai-visibility-tools.md, automation-catalog.md. - skills/seo/SKILL.md: becomes parallel dispatcher. Collects context once (depth + business), spawns both agents in a single message for concurrent execution, merges envelopes into unified SEO.md. Includes authoritative file-ownership matrix to prevent parallel-edit races. - skills/geo/SKILL.md: new standalone wrapper for GEO-only audits. Scoring - Combined score: GLOBAL = 0.80 * SEO + 0.20 * GEO (local B2C), 0.75 * SEO + 0.25 * GEO (SaaS/national/content). - GEO axis weight raised from 5% (old) to first-class dimension. Policy - AI crawlers: permissive default (maximise AI citations). Restrictive template available for premium/regulated content. - Every user action in SEO.md section 11 must cite automation options from automation-catalog.md. Tools - WebFetch + WebSearch added to allowed-tools of both skills and both agents (needed for live CWV via PageSpeed API, AI visibility testing, Wikidata/Knowledge Panel lookups, competitor analysis). Research basis (2026 state of the art validated via WebSearch): - Core Web Vitals 2.0 (VSI signal, Google core update March 2026) - AI Overviews trigger on ~48% of Google searches - ClaimReview + 6 other schema types deprecated June 2025 - Definition Lead Architecture (CMU KDD 2024, +impression score) - Citations + stats add up to 40% AI visibility (Aggarwal 2024) - Wikidata grounds every major LLM (ChatGPT, Claude, Gemini, Perplexity) Backup - agents/seo-analyzer.md.bak kept for rollback reference. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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# SEO/GEO shared resources
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Knowledge base shared by `seo-analyzer` and `geo-analyzer` agents.
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Loaded on demand — keep each file focused and current.
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| File | Owner agents | Topic |
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|---|---|---|
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| `ai-crawlers-2026.md` | seo + geo | User-agent strings, categories (training vs search), robots.txt strategy |
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| `llms-txt-template.md` | geo | `/llms.txt` + `/llms-full.txt` structure, generation patterns |
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| `geo-schemas.md` | geo | Schema.org types for AI extraction (QAPage, Speakable, Person, Article) + deprecated list |
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| `entity-seo.md` | geo | Wikidata QID, sameAs network, Knowledge Graph wiring |
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| `content-shape-for-ai.md` | geo | Definition Lead, TL;DR, Q→A, stats, citations — content patterns LLMs cite |
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| `ai-visibility-tools.md` | geo | Monitoring tools (OtterlyAI, Peec, Trendos, ZipTie, HubSpot AEO, SE Ranking) |
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| `automation-catalog.md` | seo + geo | For every user-action in SEO.md §11 — what tool can automate it |
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## Update policy
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These files capture state as of 2026-04. Crawler lists, Schema.org
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deprecations, and tool landscape shift fast. Agents MUST cross-check
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via WebSearch on each run when FULL depth is selected.
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## Loading pattern
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Agents reference resources like this:
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```
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Load: ~/.claude/agents/resources/ai-crawlers-2026.md
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```
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Do not inline these contents into agent prompts — read them at step time.
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# AI crawlers — 2026 reference
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State as of 2026-04. Cross-check via WebSearch on FULL audits — new
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bots and renames ship monthly.
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## The two categories that matter
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The blanket "block AI" strategy of 2024 is obsolete. Bots now split
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into two roles, and treating them the same loses traffic.
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### Training bots — scrape content to train future models
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No direct user traffic. No citation back. Content vanishes into weights.
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| User-agent | Company | Notes |
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|---|---|---|
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| `GPTBot` | OpenAI | Training for GPT models |
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| `Google-Extended` | Google | Opt-out for Gemini training |
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| `CCBot` | Common Crawl | Feeds many LLMs (open dataset) |
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| `anthropic-ai` | Anthropic | Legacy training bot (being phased out) |
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| `ClaudeBot` | Anthropic | Current training bot |
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| `Bytespider` | ByteDance / TikTok | Aggressive scraper, frequent complaints |
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| `Meta-ExternalAgent` | Meta | Training for Llama family |
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| `Meta-ExternalFetcher` | Meta | Per-request fetch |
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| `Applebot-Extended` | Apple | Opt-out for Apple Intelligence training |
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| `Amazonbot` | Amazon | Alexa + internal LLMs |
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| `cohere-ai` | Cohere | Training |
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| `Diffbot` | Diffbot | Knowledge Graph construction |
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| `omgilibot` | Webz.io | Data resale |
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| `img2dataset` | Various | Image dataset builders |
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| `Timpibot` | Timpi | Search-index + training hybrid |
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### Search / retrieval bots — fetch content to cite in live answers
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User asked a question → bot fetches → cites your URL → traffic returns.
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| User-agent | Company | Notes |
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|---|---|---|
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| `OAI-SearchBot` | OpenAI | Powers ChatGPT Search |
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| `ChatGPT-User` | OpenAI | On-demand fetch when user asks ChatGPT about a URL |
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| `Claude-SearchBot` | Anthropic | Powers Claude web search |
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| `Claude-User` | Anthropic | On-demand fetch inside Claude |
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| `Claude-Web` | Anthropic | Legacy retrieval bot |
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| `PerplexityBot` | Perplexity | Index builder |
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| `Perplexity-User` | Perplexity | On-demand fetch |
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| `GoogleOther` | Google | Various Google retrieval use cases |
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| `FacebookBot` | Meta | Meta AI search |
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| `DuckAssistBot` | DuckDuckGo | DuckAssist answers |
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| `YouBot` | You.com | You.com retrieval |
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| `MistralAI-User` | Mistral | On-demand fetch |
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## Recommended default strategy — PERMISSIVE
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Rationale: the user's stated goal is to maximise AI visibility. The
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future-of-search brief favours being cited over being protected.
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```
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# robots.txt — PERMISSIVE default (allow everything, block problem bots)
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# --- Training bots: allow (contributes to brand visibility long-term) ---
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User-agent: GPTBot
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Allow: /
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User-agent: Google-Extended
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Allow: /
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User-agent: ClaudeBot
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Allow: /
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User-agent: Applebot-Extended
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Allow: /
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User-agent: Meta-ExternalAgent
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Allow: /
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User-agent: CCBot
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Allow: /
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# --- Search / retrieval bots: always allow (direct traffic) ---
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User-agent: OAI-SearchBot
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Allow: /
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User-agent: ChatGPT-User
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Allow: /
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User-agent: Claude-SearchBot
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Allow: /
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User-agent: Claude-User
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Allow: /
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User-agent: PerplexityBot
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Allow: /
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User-agent: Perplexity-User
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Allow: /
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# --- Block only known-abusive bots (aggressive scraping, no return value) ---
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User-agent: Bytespider
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Disallow: /
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User-agent: omgilibot
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Disallow: /
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User-agent: img2dataset
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Disallow: /
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# --- Default: allow the rest ---
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User-agent: *
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Allow: /
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Sitemap: https://example.com/sitemap.xml
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```
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## Alternative — RESTRICTIVE (for premium content, paywalled, regulated)
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```
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# robots.txt — RESTRICTIVE (block training, allow retrieval)
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# Block all training bots
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User-agent: GPTBot
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Disallow: /
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User-agent: Google-Extended
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Disallow: /
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User-agent: ClaudeBot
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Disallow: /
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User-agent: anthropic-ai
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Disallow: /
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User-agent: CCBot
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Disallow: /
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User-agent: Bytespider
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Disallow: /
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User-agent: Meta-ExternalAgent
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Disallow: /
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User-agent: Applebot-Extended
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Disallow: /
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User-agent: Amazonbot
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Disallow: /
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User-agent: cohere-ai
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Disallow: /
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User-agent: Diffbot
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Disallow: /
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User-agent: Timpibot
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Disallow: /
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# Allow search/retrieval (keeps citations flowing)
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User-agent: OAI-SearchBot
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Allow: /
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User-agent: ChatGPT-User
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Allow: /
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User-agent: Claude-SearchBot
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Allow: /
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User-agent: Claude-User
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Allow: /
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User-agent: PerplexityBot
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Allow: /
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User-agent: Perplexity-User
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Allow: /
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User-agent: *
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Allow: /
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Sitemap: https://example.com/sitemap.xml
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```
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## Common mistakes
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- **Only blocking `ClaudeBot`** — does not block `Claude-SearchBot` or `Claude-User`. Same for other families.
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- **Using `GPTBot` to block ChatGPT Search** — wrong. `OAI-SearchBot` and `ChatGPT-User` are the search bots.
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- **Blocking `CCBot`** — has knock-on effects across dozens of downstream LLMs that train on Common Crawl.
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- **Using wildcards** (e.g. `User-agent: *AI*`) — robots.txt wildcards are not universally supported.
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- **Relying on meta robots** — `<meta name="robots">` is less respected than robots.txt by AI crawlers. Use both.
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## Verification
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Each bot should return 200 for allowed, 403 for blocked, via simulated requests:
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```bash
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DOMAIN="example.com"
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for UA in "GPTBot" "ClaudeBot" "PerplexityBot" "OAI-SearchBot" "ChatGPT-User" "Google-Extended"; do
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CODE=$(curl -sI -A "$UA" -o /dev/null -w "%{http_code}" "https://$DOMAIN/")
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echo "$UA: $CODE"
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done
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```
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This hits the page, not robots.txt directly — but if the origin respects
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robots.txt via CDN/WAF rules, you'll see the difference.
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## Sources to refresh this doc
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- https://platform.openai.com/docs/bots
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- https://darkvisitors.com/agents (community-maintained)
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- https://github.com/ai-robots-txt/ai.robots.txt
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- Anthropic docs: https://docs.anthropic.com/
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- Cloudflare AI crawlers dashboard (if account available)
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@@ -0,0 +1,99 @@
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# AI visibility monitoring tools — 2026
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Tools that track whether your brand appears in AI-generated answers
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across ChatGPT, Perplexity, Gemini, Copilot, Claude, and Google AI
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Overviews.
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Context: Google AI Overviews trigger on ~48% of searches; ChatGPT
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processes 2.5B queries/day; Gartner projects commercial organic
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search traffic will drop 25% by 2026. Monitoring is no longer optional.
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## Commercial tools
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| Tool | Platforms covered | Strong points | Weak points |
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|---|---|---|---|
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| **OtterlyAI** (otterly.ai) | ChatGPT, Perplexity, Gemini, AI Overviews, Copilot | Mature, 20k+ users, Gartner-recognised | Pricing mid-to-high |
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| **Peec AI** (peec.ai) | ChatGPT, Perplexity, Gemini, AI Overviews | Good SaaS-brand focus, sentiment analysis | Narrower platform scope |
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| **Profound** (tryprofound.com) | ChatGPT, Perplexity, Gemini, Copilot | Enterprise-grade, full-response capture | Enterprise pricing |
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| **ZipTie** (ziptie.dev) | ChatGPT, Perplexity, AI Overviews | Competitive benchmarking, source attribution | Smaller team, newer |
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| **HubSpot AEO** (hubspot.com/products/aeo) | ChatGPT, Gemini, Perplexity | Integrates with HubSpot ecosystem | Best if already HubSpot user |
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| **Trendos** (trendos by Tesonet) | ChatGPT, Gemini, AI Search, Perplexity, DeepSeek | Added DeepSeek coverage, 2026 launch | Unproven longevity |
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| **SE Ranking AI Tracker** (seranking.com) | ChatGPT, Perplexity, Gemini, AI Mode, AI Overviews | Bundled with classical SEO suite | Less specialised |
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| **LLMrefs** (llmrefs.com) | ChatGPT, Perplexity, Gemini, Claude | GEO focus, research-backed | Newer, less tested |
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## Free / manual methods (zero budget)
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For clients/projects with no monitoring budget, a manual process works
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at lower frequency. Recommended cadence: monthly for established
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brands, weekly during optimization sprints.
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### Query list construction
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Build a list of 20-40 queries covering:
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1. **Branded queries** — "what is [brand]", "is [brand] good", "[brand] reviews"
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2. **Generic category queries** — "best [category] in [location]", "how to [problem]"
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3. **Comparison queries** — "[brand] vs [competitor]", "alternatives to [brand]"
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4. **Problem queries** — the actual questions the target persona asks
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### Manual check workflow
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For each query, run across:
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- **ChatGPT** (web version with search enabled, chatgpt.com)
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- **Perplexity** (perplexity.ai)
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- **Google AI Overviews** (google.com — appears for ~48% of searches)
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- **Claude** (claude.ai with web search)
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- **Gemini** (gemini.google.com)
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- **Copilot** (copilot.microsoft.com)
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- **Brave Search AI** (search.brave.com)
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- **DuckAssist** (duckduckgo.com)
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Record for each:
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- Mentioned? (yes/no)
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- Cited with link? (yes/no + which page)
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- Position in answer? (1st mention / buried / listed)
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- Sentiment? (positive / neutral / negative / misleading)
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### Spreadsheet template
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| Date | Query | ChatGPT | Perplexity | Google AIO | Claude | Gemini | Copilot |
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|---|---|---|---|---|---|---|---|
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| 2026-04-21 | best plombier Évry | Mentioned, ranked 3, cited | Not mentioned | Top 3, no cite | — | — | — |
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## KPIs to track
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From GEO research and industry consensus (GenOptima, HubSpot 2026):
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| Metric | Definition | Benchmark |
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|---|---|---|
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| **Mention Rate** | % of AI answers that mention brand name | Varies; track trend, not absolute |
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| **Citation Rate** | % of AI answers with a clickable link to domain | Target 20%+ for established brands |
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| **Position** | When cited, is brand 1st mention vs buried? | First mention = best |
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| **Sentiment** | Tone of brand mention (positive/neutral/negative) | Track for negative drift |
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| **Source Diversity** | Which of your pages get cited? | Aim for 5+ distinct pages/domain |
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| **Competitor Share** | % of category queries where competitor cited vs brand | Track gap |
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## Integration into SEO.md
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In `SEO.md §11 — Actions utilisateur requises`:
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> ### Monitor AI visibility monthly
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>
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> **Automatisation possible avec:** OtterlyAI, Peec AI, ZipTie, HubSpot
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> AEO, SE Ranking AI Tracker. Budget: 50-500 EUR/mois selon le tool.
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>
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> **Alternative manuelle gratuite:** template spreadsheet + 20 queries
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> testées mensuellement sur ChatGPT, Perplexity, Google AI Overviews.
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> Temps: ~1h/mois.
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## Methodology caveats
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- AI engines are **non-deterministic**. Same query twice can return
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different answers. Always take 3 samples and track the median.
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- **Personalisation** affects results. Test in logged-out / private
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mode for reproducibility.
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- **Geographic bias** — ChatGPT's answers about local businesses vary
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by IP. Test from the target market's geography.
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- **Freshness lag** — content updates take days to weeks to propagate
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into AI answers. Don't expect instant reflection of changes.
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# Automation catalog — for SEO.md §11 user actions
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For every action that requires the human, this catalog lists tools
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that can partially or fully automate it. Both agents cite this file
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when emitting user actions into `SEO.md §11`.
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**Format rule in SEO.md §11**: every entry MUST include:
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```
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- **<Action>** — <what to do>
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**Automatisation possible avec:** <tool 1>, <tool 2>, <tool 3>
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**Budget:** <free / XX EUR/mois / one-time XX EUR>
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**Effort manuel:** <time estimate>
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```
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## Local SEO actions
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### Google Business Profile — claim / create / optimize
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- **Google Business Profile API** (free, requires Google Cloud project)
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→ post updates, reply to reviews, sync hours automatically
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- **Yext** (enterprise, 500-5000 EUR/mois) → syncs GMB across
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200+ directories
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- **BrightLocal** (30-80 USD/mois) → GMB management + rank tracking
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- **Moz Local** (14-33 USD/mois/location) → listing management
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- **Uberall** (enterprise) → multi-location listing sync
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- **LocalFalcon** (30-60 USD/mois) → GMB rank visualisation
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- **PlePer** (~25 EUR/mois) → GMB post scheduling
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- Manual workflow: 30 min/week via https://business.google.com
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### Review management — collect, reply, aggregate
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- **Trustpilot / Google Reviews API** (via GBP API) → read/reply programmatically
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- **Birdeye** (290+ USD/mois) → review aggregation + auto-reply
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- **Podium** (enterprise) → SMS-based review requests
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- **NiceJob** (90 USD/mois) → review request automation
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- **Grade.us** (110 USD/mois) → multi-platform aggregation
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- Manual: monitor GMB + reply within 48h (legal: L121-1 Code conso FR)
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### Directory citations — PagesJaunes, Yelp, Mappy, Bing Places, Apple
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|
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- **Yext** → 200+ directories incl. French
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- **BrightLocal / Moz Local** → coverage varies, check French support
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- **Uberall** → strong in European markets
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- **Rio SEO** (enterprise) → big brands
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- Manual: one-time 4-8h to register on top 10 directories
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## AI visibility actions
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### Monitor brand in AI engines
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|
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See `ai-visibility-tools.md`. Summary:
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- **OtterlyAI, Peec AI, Trendos, ZipTie, HubSpot AEO, SE Ranking** — commercial
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- **Manual spreadsheet + 20 queries/mois** — free, ~1h/mois
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### Submit to AI indexes directly
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- **Bing Webmaster Tools** → submits to Bing + Copilot + ChatGPT Search (which uses Bing index)
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- **IndexNow protocol** (indexnow.org) → proactive ping to Bing/Yandex
|
||||
- **Google Search Console + URL Inspection** → request indexing (no ChatGPT index direct submit exists in 2026)
|
||||
|
||||
### Maintain llms.txt / llms-full.txt
|
||||
|
||||
- **llms-txt-action** (GitHub Action) → rebuild on deploy
|
||||
- **Mintlify / Fern / ReadMe** → auto-generated for supported docs hosts
|
||||
- **Custom cron + script** → pull from CMS, regenerate weekly
|
||||
- Manual: monthly review if content changes rarely
|
||||
|
||||
## Entity / Knowledge Graph actions
|
||||
|
||||
### Create or optimize Wikidata entry
|
||||
|
||||
- **Kalicube** (commercial, custom pricing) → specialised Knowledge Panel + Wikidata
|
||||
- **InLinks** (40-350 USD/mois) → entity optimization + Schema.org graph
|
||||
- **WordLift** (30-300 USD/mois) → WordPress plugin with Wikidata linking
|
||||
- **Entity.ai** → entity signal auditing
|
||||
- Manual: https://www.wikidata.org, 2-4h initial + sources required
|
||||
|
||||
### Claim / optimize Google Knowledge Panel
|
||||
|
||||
- **Kalicube** — best specialisation
|
||||
- **Manual via Google Search** — click "Claim this Knowledge Panel" (requires verification)
|
||||
- Cannot be forced; appears when entity signals are strong enough
|
||||
|
||||
### LinkedIn / Crunchbase / industry directory entities
|
||||
|
||||
- **Yext** → includes Crunchbase sync in enterprise tiers
|
||||
- **Manual** → LinkedIn Company page free, Crunchbase free profile claim
|
||||
- **Brandify** (enterprise) → multi-directory entity management
|
||||
|
||||
## Content production actions
|
||||
|
||||
### Create city/service landing pages (30/70 rule)
|
||||
|
||||
- **Surfer SEO** (89-219 USD/mois) → content optimization with AI
|
||||
- **Frase.io** (45-115 USD/mois) → SERP-driven briefs
|
||||
- **Clearscope** (170+ USD/mois) → keyword + semantic briefs
|
||||
- **Manual + AI writer** → use Claude/ChatGPT with explicit 30/70 instruction
|
||||
|
||||
Agent note: Batch D in `seo-analyzer` triage can handle the
|
||||
CREATION of these pages if confirmation granted — city pages are
|
||||
typically batch D (structural change, user approval needed).
|
||||
|
||||
### Produce blog content on schedule
|
||||
|
||||
- **Frase / Surfer / Clearscope** (see above)
|
||||
- **MarketMuse** (enterprise) → content planning
|
||||
- **Jasper AI / Copy.ai** → AI drafting (quality review mandatory)
|
||||
- Human editor remains the bottleneck — AI drafts need domain expert review
|
||||
|
||||
### Refresh existing content quarterly
|
||||
|
||||
- **ContentKing** (now part of Conductor) → change detection
|
||||
- **SEOClarity** (enterprise) → content decay tracking
|
||||
- **Manual** — spreadsheet of top 50 pages + quarterly review cycle
|
||||
|
||||
## Technical SEO actions
|
||||
|
||||
### Generate sitemaps
|
||||
|
||||
- **Framework plugin** — `@astrojs/sitemap`, `next-sitemap`, `@nuxtjs/sitemap`, `rails-sitemap-generator`, etc.
|
||||
- **Yoast / RankMath** (WordPress) → auto-generate
|
||||
- **Screaming Frog** (200 GBP/an) → crawler-based generation
|
||||
- Manual: only as last resort, hand-maintained sitemaps go stale fast
|
||||
|
||||
### Implement Schema.org at scale
|
||||
|
||||
- **Yoast / RankMath / SEOPress** (WordPress) → Article/Organization/LocalBusiness auto-graph
|
||||
- **Schema App** (enterprise) → multi-CMS
|
||||
- **Merkle Schema Markup Generator** (free) → one-off generation
|
||||
- **Manual + `geo-schemas.md` templates** — for frameworks without plugins
|
||||
|
||||
### Optimize Core Web Vitals
|
||||
|
||||
- **PageSpeed Insights API** (free) → measure + monitor
|
||||
- **WebPageTest** (free tier + paid) → detailed waterfalls
|
||||
- **Cloudflare Speed** (free tier with Cloudflare) → CDN-level optimizations
|
||||
- **Nitropack** (35-175 USD/mois) → WordPress speed automation
|
||||
- **Vercel Speed Insights** (free for Vercel projects)
|
||||
- Manual: Lighthouse + manual fixes guided by its recommendations
|
||||
|
||||
### Security headers (CSP, HSTS, X-Frame-Options, Referrer-Policy)
|
||||
|
||||
- **securityheaders.com** (free audit)
|
||||
- **Cloudflare Page Rules** → header injection
|
||||
- **Vercel `next.config.js` headers** → declarative
|
||||
- **`.htaccess`** → Apache hosts
|
||||
- Manual: one-time config, ~1-2h setup
|
||||
|
||||
## Social presence actions
|
||||
|
||||
### Create / maintain social profiles (Facebook, Instagram, LinkedIn, TikTok, YouTube)
|
||||
|
||||
- **Buffer** (6-120 USD/mois) → multi-platform scheduling
|
||||
- **Hootsuite** (99-249 USD/mois) → full social suite
|
||||
- **Later** (16-80 USD/mois) → visual content scheduling
|
||||
- **Metricool** (18-50 USD/mois) → analytics + scheduling
|
||||
- Manual: 30-60 min/semaine for basic maintenance
|
||||
|
||||
### Monitor brand mentions on social / forums / Reddit
|
||||
|
||||
- **Brand24** (99-299 USD/mois)
|
||||
- **Mention** (41-149 USD/mois)
|
||||
- **Google Alerts** (free, basic)
|
||||
- **Reddit search + saved queries** — free, manual
|
||||
- **BuzzSumo** (199+ USD/mois) → trend + mention discovery
|
||||
|
||||
## Legal compliance actions (FR)
|
||||
|
||||
### Install cookie consent management (CMP)
|
||||
|
||||
- **Axeptia / Axeptio** (free to 100 EUR/mois) → French-focused CMP
|
||||
- **Cookiebot** (11-96 USD/mois) → international CMP, CNIL-compliant
|
||||
- **OneTrust** (enterprise) → enterprise compliance
|
||||
- **tarteaucitron.js** (free, open source) → CNIL-compliant, self-hosted
|
||||
- **Didomi** (enterprise) → strong French legal context
|
||||
|
||||
### Generate legal pages (mentions légales, politique de confidentialité, CGV)
|
||||
|
||||
- **Legalstart / Captain Contrat** (one-time 50-200 EUR) → FR templates
|
||||
- **Genius Legal** → template generators
|
||||
- **Legalbuddy** → questionnaire-driven legal pages
|
||||
- Agent fallback: Batch B in `seo-analyzer` creates templates with
|
||||
`[À COMPLÉTER]` placeholders for SIREN, capital, etc.
|
||||
|
||||
## Reporting format in SEO.md §11
|
||||
|
||||
Example entry generated by the agents:
|
||||
|
||||
```markdown
|
||||
### Créer / réclamer la fiche Google Business Profile
|
||||
|
||||
**Action:** Vérifier que la fiche GMB existe, est réclamée, et les
|
||||
informations sont cohérentes avec le site (NAP).
|
||||
|
||||
**Lien direct:** https://business.google.com
|
||||
|
||||
**Automatisation possible avec:**
|
||||
- Google Business Profile API (gratuit, technique)
|
||||
- BrightLocal (30-80 USD/mois, gestion + rank tracking)
|
||||
- Yext (500+ EUR/mois, multi-directories)
|
||||
- LocalFalcon (30-60 USD/mois, rank visualisation)
|
||||
|
||||
**Effort manuel:** 30 min initial + 30 min/semaine maintenance
|
||||
**Impact SEO local:** critique (base du SEO local)
|
||||
```
|
||||
|
||||
## Maintenance of this catalog
|
||||
|
||||
Tool landscape shifts fast. Cross-check quarterly:
|
||||
- Have tool URLs changed?
|
||||
- Has pricing moved tier?
|
||||
- Have new tools emerged (especially in AI visibility monitoring)?
|
||||
- Are deprecated tools still listed?
|
||||
|
||||
Use WebSearch on FULL audits to validate before emitting in SEO.md.
|
||||
@@ -0,0 +1,250 @@
|
||||
# Content shape for LLM extraction
|
||||
|
||||
How to write pages so AI engines quote, cite, and recommend them.
|
||||
Based on peer-reviewed GEO research (CMU KDD 2024, Aggarwal et al.)
|
||||
and tracked citation patterns across ChatGPT, Perplexity, Claude,
|
||||
Gemini, Google AI Overviews (2025-2026).
|
||||
|
||||
## The six patterns that measurably increase AI citations
|
||||
|
||||
### 1. Definition Lead Architecture
|
||||
|
||||
Open the page (or first paragraph after each major heading) with:
|
||||
|
||||
> **[Entity] is a [category] that [differentiator].**
|
||||
|
||||
Research backing: CMU GEO framework (KDD 2024) — pages with explicit
|
||||
definitional openings score significantly higher in LLM retrieval
|
||||
impression scores.
|
||||
|
||||
**Good**: "Astro is a static site generator that ships zero JavaScript by default, producing HTML at build time that search engines and AI crawlers can index without running a browser."
|
||||
|
||||
**Bad**: "In today's fast-paced digital landscape, choosing the right framework can feel overwhelming. At Acme, we know how important it is to..."
|
||||
|
||||
### 2. TL;DR / Answer Box above the fold
|
||||
|
||||
Insert an explicit summary block at the top of long content. AI engines
|
||||
preferentially quote from these blocks because the content is
|
||||
pre-summarised.
|
||||
|
||||
```html
|
||||
<aside class="tldr">
|
||||
<strong>TL;DR</strong> —
|
||||
Next.js 15 removes the pages/ directory entirely in favour of App
|
||||
Router. Migration requires rewriting route handlers, layouts, and
|
||||
data fetching. Estimated effort: 2-5 days for a medium project.
|
||||
</aside>
|
||||
```
|
||||
|
||||
CSS: no class requirement, but mark it semantically (e.g. `aria-label="summary"`
|
||||
or Speakable schema targeting this selector).
|
||||
|
||||
### 3. Question-then-direct-answer structure
|
||||
|
||||
Each H2/H3 heading phrased as a likely user query. First sentence
|
||||
after the heading: a single-sentence direct answer. Supporting detail
|
||||
follows.
|
||||
|
||||
**Pattern**:
|
||||
```
|
||||
## How much does a Qualibat RGE certification cost in France?
|
||||
|
||||
A Qualibat RGE certification costs between 500 and 1500 EUR for the
|
||||
initial audit, plus an annual fee of 200-400 EUR. The cost varies by
|
||||
trade category and company size.
|
||||
|
||||
[Detailed breakdown follows...]
|
||||
```
|
||||
|
||||
Why it works: LLMs grade passages by answer-density relative to the
|
||||
query. A one-sentence self-contained answer has the highest density.
|
||||
|
||||
### 4. Citations and statistics (strongest measured lever)
|
||||
|
||||
Adding peer-cited statistics with clear sources increases AI visibility
|
||||
**by up to 40%** (Aggarwal et al., 2024 "GEO: Generative Engine
|
||||
Optimization").
|
||||
|
||||
Pattern: embed specific numbers with attribution.
|
||||
|
||||
**Good**: "According to the ADEME 2024 energy report, French households spent an average of 2,137 EUR on heating in 2023 — a 12% increase from 2021."
|
||||
|
||||
**Bad**: "Heating costs have increased a lot recently."
|
||||
|
||||
Source attribution matters: link the citation to the original source
|
||||
(`<a href>`), ideally with `rel="cite"`. AI engines use link graphs
|
||||
to validate factual claims.
|
||||
|
||||
### 5. Structured lists and comparison tables
|
||||
|
||||
LLMs quote list items and table rows more readily than prose of the
|
||||
same content. Convert what you can:
|
||||
|
||||
**Before** (prose):
|
||||
"The best frameworks for public sites are Astro for static content,
|
||||
Next.js for dynamic server-rendered apps, and Nuxt for Vue-based
|
||||
projects."
|
||||
|
||||
**After** (list):
|
||||
"Best frameworks for public sites by use case:
|
||||
- **Astro** — static content (blog, docs, portfolio)
|
||||
- **Next.js** — dynamic SSR with React
|
||||
- **Nuxt** — dynamic SSR with Vue"
|
||||
|
||||
Comparison tables are even stronger. Structure:
|
||||
|
||||
| Framework | Rendering | Best for | JS by default |
|
||||
|---|---|---|---|
|
||||
| Astro | SSG + islands | Public content | 0 KB |
|
||||
| Next.js | SSG + SSR | Hybrid apps | Large |
|
||||
|
||||
### 6. Freshness signals
|
||||
|
||||
Pages not updated at least quarterly are **3x more likely to lose AI
|
||||
citations** (LLMRefs 2026 study).
|
||||
|
||||
What to maintain:
|
||||
- Visible "Last updated: YYYY-MM-DD" at the top of content pages
|
||||
- `dateModified` in Article/BlogPosting JSON-LD (ISO 8601)
|
||||
- HTTP header `Last-Modified` in sync with content change
|
||||
- Changelog on evergreen reference pages
|
||||
|
||||
Do NOT fake dates — AI engines and Google increasingly validate
|
||||
freshness against actual content diffs.
|
||||
|
||||
## Anti-patterns — what to avoid
|
||||
|
||||
### Pronoun-heavy writing
|
||||
|
||||
LLMs resolve pronouns by context window, which costs them confidence.
|
||||
Prefer explicit entity names.
|
||||
|
||||
**Bad**: "It was founded in 2015. Its founders wanted to solve a problem. They saw that..."
|
||||
|
||||
**Good**: "Acme Corp was founded in 2015. Acme's founders, Jane Doe and John Smith, wanted to solve..."
|
||||
|
||||
### Marketing fluff before facts
|
||||
|
||||
AI engines typically truncate retrieval windows. Fluff at the top
|
||||
wastes the budget. Put factual claims FIRST.
|
||||
|
||||
**Bad** (first 200 chars wasted): "In today's fast-moving digital landscape, businesses are constantly looking for ways to stay competitive..."
|
||||
|
||||
**Good** (first 200 chars dense): "Our API processes 50M requests/day at p99 latency of 47ms across 8 regions, with a 99.99% SLA. Pricing starts at 99 EUR/month for the 10K requests tier."
|
||||
|
||||
### Claims without sources
|
||||
|
||||
Any numerical or comparative claim without a linked source degrades
|
||||
trust. AI engines can detect the pattern "number without citation" and
|
||||
weight those passages lower.
|
||||
|
||||
### Cookie-cutter content across pages (especially city pages)
|
||||
|
||||
The 30/70 rule: when creating per-city or per-service variants,
|
||||
at most 30% of the content should be templated. 70% must be
|
||||
unique per page (local landmarks, specific testimonials, unique
|
||||
stats, real photos).
|
||||
|
||||
Generic city pages get filtered out as "doorway pages" by both
|
||||
classical search and AI engines.
|
||||
|
||||
## Page templates by type
|
||||
|
||||
### Service page (local business)
|
||||
|
||||
```
|
||||
<h1>[Service] in [City] — [Business Name]</h1>
|
||||
|
||||
<div class="tldr">
|
||||
<strong>En résumé :</strong> [Business] offers [service] in [city + surrounding].
|
||||
[Key differentiator — price, response time, certifications]. Open [hours].
|
||||
Call [phone] or request a quote online.
|
||||
</div>
|
||||
|
||||
<h2>What is [service]?</h2>
|
||||
<p>[Service] is a [category] that [differentiator]. In [city], demand
|
||||
is driven by [local factor — housing stock, climate, regulations].</p>
|
||||
|
||||
<h2>How much does [service] cost in [city]?</h2>
|
||||
<p>[Specific price range] for a typical [job type], based on [n]
|
||||
projects completed in [year]. Factors affecting cost: [list].</p>
|
||||
|
||||
<h2>Why choose [Business] for [service]?</h2>
|
||||
<ul>
|
||||
<li>[Certification 1] — [what it means]</li>
|
||||
<li>[Certification 2]</li>
|
||||
<li>[N+ years] experience on [specific housing stock]</li>
|
||||
</ul>
|
||||
|
||||
<h2>FAQ</h2>
|
||||
[QAPage or FAQPage schema + visible Q&A]
|
||||
```
|
||||
|
||||
### Blog post / guide
|
||||
|
||||
```
|
||||
<h1>[Clear, question-style or noun-phrase headline]</h1>
|
||||
<p class="byline">By [Author Name] — Updated [Date]</p>
|
||||
|
||||
<div class="tldr">
|
||||
[3-5 sentence summary. Include the key number, the key conclusion,
|
||||
and any nuance.]
|
||||
</div>
|
||||
|
||||
<h2>[Question 1]</h2>
|
||||
<p>[One-sentence answer.] [Supporting detail with cited statistics.]</p>
|
||||
|
||||
<h2>[Question 2]</h2>
|
||||
...
|
||||
|
||||
<h2>Sources</h2>
|
||||
<ul>
|
||||
<li><a href="...">Source 1 — author, year</a></li>
|
||||
<li><a href="...">Source 2 — author, year</a></li>
|
||||
</ul>
|
||||
```
|
||||
|
||||
### Homepage / landing
|
||||
|
||||
```
|
||||
<h1>[Entity] is a [category] that [differentiator].</h1>
|
||||
<!-- The H1 IS the Definition Lead. Yes, really. -->
|
||||
|
||||
<p class="hero-subtitle">
|
||||
[Elaboration on the H1. Include one concrete stat or proof point.]
|
||||
</p>
|
||||
|
||||
[Primary CTA]
|
||||
|
||||
<section>
|
||||
<h2>What [Entity] does</h2>
|
||||
<p>[Functional description, one paragraph.]</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>Who uses [Entity]</h2>
|
||||
<ul><li>[Use case 1]</li><li>[Use case 2]</li>...</ul>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>How it works</h2>
|
||||
<!-- HowTo schema + visible steps -->
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h2>Frequently asked</h2>
|
||||
<!-- FAQPage schema + visible Q&A -->
|
||||
</section>
|
||||
```
|
||||
|
||||
## Self-audit — is this page AI-friendly?
|
||||
|
||||
- [ ] First sentence: `[Entity] is a [category] that [differentiator]` ?
|
||||
- [ ] TL;DR or summary block above the fold ?
|
||||
- [ ] Every H2/H3 phrased as a likely user question ?
|
||||
- [ ] First sentence under each heading: direct answer ?
|
||||
- [ ] At least 2-3 specific numerical claims with linked sources ?
|
||||
- [ ] Visible "Last updated" date + matching `dateModified` in JSON-LD ?
|
||||
- [ ] Lists or tables instead of dense prose where possible ?
|
||||
- [ ] Entity names used explicitly, not pronouns ?
|
||||
- [ ] If it's a city/service variant: ≥70% unique content ?
|
||||
@@ -0,0 +1,163 @@
|
||||
# Entity SEO — Wikidata, Knowledge Graph, sameAs
|
||||
|
||||
Why this matters: every major AI engine (ChatGPT, Claude, Gemini,
|
||||
Perplexity, Apple Intelligence) grounds factual claims against
|
||||
Wikidata. A business without a clean entity footprint is effectively
|
||||
invisible to AI grounding pipelines, regardless of on-site SEO.
|
||||
|
||||
## The entity identity stack
|
||||
|
||||
Think of your entity as having five layers, from strongest to weakest
|
||||
identity signal:
|
||||
|
||||
1. **Wikidata QID** — globally unique, machine-readable identifier.
|
||||
2. **Wikipedia article** — human-readable notability signal.
|
||||
3. **Google Knowledge Panel** — surfaced directly in Google results.
|
||||
4. **Authoritative third-party IDs** — Crunchbase, Bloomberg, SIRENE (FR), Companies House (UK), OpenCorporates.
|
||||
5. **Social + directory profiles** — LinkedIn, Facebook, PagesJaunes, industry directories.
|
||||
|
||||
Each layer reinforces the ones below. Wikidata is the most leveraged
|
||||
because it's structured, open, and explicitly consumed by LLMs.
|
||||
|
||||
## Audit checklist
|
||||
|
||||
### Does the entity have a Wikidata QID?
|
||||
|
||||
Search: https://www.wikidata.org/wiki/Special:Search — by name + city.
|
||||
|
||||
If found:
|
||||
- Record QID (format `Q` + number, e.g. `Q12345678`)
|
||||
- Verify: official website property (P856) points to the current domain
|
||||
- Verify: VAT (P3608), SIRET (P3893), category (P31) are correct
|
||||
|
||||
If NOT found:
|
||||
- For businesses meeting Wikidata notability: creation is possible
|
||||
(requires verifiable third-party sources)
|
||||
- For non-notable businesses: skip Wikidata, focus on other identity layers
|
||||
- Flag in SEO.md §11 as user action (Wikidata requires human judgement
|
||||
+ source citations)
|
||||
|
||||
### Does the entity have a Wikipedia article?
|
||||
|
||||
- Search by exact business name. If found and matches: record URL.
|
||||
- If not found: flag as long-term goal (long-term — notability bar is high).
|
||||
|
||||
### Is there a Google Knowledge Panel?
|
||||
|
||||
Search Google: exact business name. Look for the right-side panel.
|
||||
|
||||
- Present + claimed → verify info is correct
|
||||
- Present + unclaimed → user action: claim via https://www.google.com/business/
|
||||
- Absent → Knowledge Panels are generated automatically when entity
|
||||
signals are strong enough (GMB + Wikidata + consistent citations)
|
||||
|
||||
### Is `sameAs` complete in on-site JSON-LD?
|
||||
|
||||
The `sameAs` property is how you declare "these external URLs represent
|
||||
the same entity as this page". It's the single most impactful entity
|
||||
signal after Wikidata.
|
||||
|
||||
Minimum recommended `sameAs` for a local business:
|
||||
```json
|
||||
"sameAs": [
|
||||
"https://www.wikidata.org/wiki/Q123456789", // if exists
|
||||
"https://www.linkedin.com/company/name",
|
||||
"https://www.facebook.com/businessname",
|
||||
"https://www.instagram.com/businessname",
|
||||
"https://www.pagesjaunes.fr/pros/12345", // FR
|
||||
"https://fr.wikipedia.org/wiki/Nom_Entreprise" // if exists
|
||||
]
|
||||
```
|
||||
|
||||
For a SaaS / international brand, add:
|
||||
```json
|
||||
"https://www.crunchbase.com/organization/name",
|
||||
"https://github.com/organization",
|
||||
"https://www.g2.com/products/name",
|
||||
"https://www.producthunt.com/products/name"
|
||||
```
|
||||
|
||||
For a Person (author, founder):
|
||||
```json
|
||||
"sameAs": [
|
||||
"https://www.wikidata.org/wiki/Q987654321",
|
||||
"https://www.linkedin.com/in/name",
|
||||
"https://twitter.com/name",
|
||||
"https://github.com/name",
|
||||
"https://scholar.google.com/citations?user=XYZ", // academics
|
||||
"https://orcid.org/0000-0000-0000-0000" // academics
|
||||
]
|
||||
```
|
||||
|
||||
### Is `@id` used consistently?
|
||||
|
||||
Across all JSON-LD blocks on the site, the same entity MUST use the
|
||||
same `@id`. Pattern: `https://example.com/#org` for the organization,
|
||||
`https://example.com/about#author-{slug}` for people.
|
||||
|
||||
Split across multiple pages? Use `@id` with fragment identifiers to
|
||||
tie them back to one canonical entity node.
|
||||
|
||||
## The Wikidata playbook for businesses
|
||||
|
||||
Not every business qualifies for Wikidata. Criteria (simplified):
|
||||
- Multiple independent third-party sources (press articles, books,
|
||||
academic papers) covering the entity.
|
||||
- Some form of public notability (not just "we exist").
|
||||
|
||||
If qualified, the creation workflow:
|
||||
|
||||
1. Create Wikidata account.
|
||||
2. Use "Create a new item" → name, label, description.
|
||||
3. Add statements with sources:
|
||||
- `instance of (P31)` → `enterprise (Q6881511)` or more specific
|
||||
- `country (P17)` → `France (Q142)`
|
||||
- `headquarters location (P159)` → city QID
|
||||
- `official website (P856)` → domain URL
|
||||
- `inception (P571)` → founding date
|
||||
- `industry (P452)` → industry QID
|
||||
- `SIRET (P3893)` → SIRET number (FR)
|
||||
- `VAT number (P3608)` → VAT ID
|
||||
4. Each statement must cite a reference (URL of press article,
|
||||
official registry, etc.).
|
||||
5. Wait for community review. Items without sources get merged or deleted.
|
||||
|
||||
This is labor-intensive and failure-prone for non-notable entities.
|
||||
Do NOT invent sources. Better to skip Wikidata than create a deletable item.
|
||||
|
||||
## Automation options (for SEO.md §11)
|
||||
|
||||
- **Kalicube** — paid service specialised in Knowledge Panel + Wikidata
|
||||
optimization for businesses and executives.
|
||||
- **Entity.ai** / **InLinks** — tools that help structure entity
|
||||
signals on-site + track Knowledge Panel status.
|
||||
- **WordLift** — WordPress/plugin with Wikidata linking + Schema.org
|
||||
graph generation.
|
||||
- **Yext Knowledge Graph** — enterprise platform syncing entity data
|
||||
across 200+ directories.
|
||||
- **BrightLocal / Moz Local / Uberall** — focus on local citations
|
||||
+ directory sync (not Wikidata-specific).
|
||||
|
||||
For Wikidata specifically: no full-automation tool is reliable because
|
||||
it requires sourced statements. Human curation is the bottleneck.
|
||||
|
||||
## Common mistakes
|
||||
|
||||
- **Fake Wikidata entries** — flagged and deleted by community, damages
|
||||
reputation.
|
||||
- **`sameAs` pointing to dead profiles** — validate each URL resolves.
|
||||
- **Inconsistent entity names across platforms** ("Dupont Plomberie"
|
||||
vs "Plomberie Dupont" vs "DUPONT PLOMBERIE SAS") — pick one, apply
|
||||
everywhere.
|
||||
- **Missing VAT/SIREN on Organization schema** — easy credibility
|
||||
signal, often forgotten.
|
||||
- **Treating @id as a URL that must resolve** — `@id` is an identifier,
|
||||
not a mandatory-resolvable URL (though resolvable is better).
|
||||
|
||||
## Verification tools
|
||||
|
||||
- https://www.wikidata.org/wiki/Special:Search — find QID
|
||||
- https://tools.wmflabs.org/reasonator/ — human-readable Wikidata view
|
||||
- https://kalicube.com — commercial Knowledge Panel audit
|
||||
- https://www.google.com/search?q=%22business+name%22 — check Knowledge Panel
|
||||
- Schema validator (see `geo-schemas.md`) — check `@id` + `sameAs` integrity
|
||||
@@ -0,0 +1,343 @@
|
||||
# Schema.org for GEO — types that matter in 2026
|
||||
|
||||
All examples use JSON-LD (the only format Google recommends in 2026).
|
||||
Place inside `<script type="application/ld+json">` in `<head>` or
|
||||
before `</body>`.
|
||||
|
||||
## DEPRECATED — do not emit
|
||||
|
||||
Google deprecated these in June 2025. Stop emitting them and remove
|
||||
existing instances. They no longer produce rich results.
|
||||
|
||||
- `ClaimReview` (was a fact-check signal)
|
||||
- `CourseInfo`
|
||||
- `EstimatedSalary`
|
||||
- `LearningVideo`
|
||||
- `SpecialAnnouncement`
|
||||
- `VehicleListing`
|
||||
- `Book` actions (ReadAction, BuyAction on Book)
|
||||
|
||||
## TIER 1 — highest GEO impact
|
||||
|
||||
### QAPage — single Q&A format
|
||||
|
||||
Pages cited 58% more often by ChatGPT vs basic Article schema.
|
||||
Use when the page is built around ONE primary question.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "QAPage",
|
||||
"mainEntity": {
|
||||
"@type": "Question",
|
||||
"name": "What is the best framework for a public website in 2026?",
|
||||
"text": "Should I use React SPA, Next.js, or Astro for a public-facing website in 2026?",
|
||||
"answerCount": 1,
|
||||
"acceptedAnswer": {
|
||||
"@type": "Answer",
|
||||
"text": "For public-facing websites, Astro is the 2026 default because it ships static HTML by default, preserves SEO/GEO signals, and allows React/Vue/Svelte islands only where interactivity is needed. React SPAs are only appropriate for authenticated, non-indexed surfaces.",
|
||||
"dateCreated": "2026-04-21",
|
||||
"upvoteCount": 0,
|
||||
"author": {
|
||||
"@type": "Person",
|
||||
"name": "Author Name",
|
||||
"url": "https://example.com/about"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### FAQPage — multiple Q&A
|
||||
|
||||
Only valid when the page visibly contains all listed questions and
|
||||
answers. Google will penalise pages with FAQ schema that doesn't match
|
||||
visible content.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "FAQPage",
|
||||
"mainEntity": [
|
||||
{
|
||||
"@type": "Question",
|
||||
"name": "How long does shipping take?",
|
||||
"acceptedAnswer": {
|
||||
"@type": "Answer",
|
||||
"text": "Standard shipping takes 2 to 5 business days in France."
|
||||
}
|
||||
},
|
||||
{
|
||||
"@type": "Question",
|
||||
"name": "Do you offer refunds?",
|
||||
"acceptedAnswer": {
|
||||
"@type": "Answer",
|
||||
"text": "Yes — refunds are available within 30 days of purchase."
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### Speakable — voice + AI extraction marker
|
||||
|
||||
62% of searches in 2026 involve voice. Speakable flags the passage
|
||||
best suited for voice readout and AI summary.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "Article",
|
||||
"headline": "Article headline",
|
||||
"speakable": {
|
||||
"@type": "SpeakableSpecification",
|
||||
"cssSelector": [".article-summary", ".tldr"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Or via xpath for non-CSS-targetable content:
|
||||
```json
|
||||
"speakable": {
|
||||
"@type": "SpeakableSpecification",
|
||||
"xpath": ["/html/head/title", "//div[@class='tldr']"]
|
||||
}
|
||||
```
|
||||
|
||||
### Article + Person — E-E-A-T backbone
|
||||
|
||||
The single most important pattern for non-local content. Couples
|
||||
content to a real author with verifiable credentials.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "Article",
|
||||
"headline": "Exact title of the article",
|
||||
"description": "One-sentence summary matching meta description.",
|
||||
"image": ["https://example.com/images/hero-1x1.jpg", "https://example.com/images/hero-4x3.jpg", "https://example.com/images/hero-16x9.jpg"],
|
||||
"datePublished": "2026-04-15T09:00:00+02:00",
|
||||
"dateModified": "2026-04-21T14:30:00+02:00",
|
||||
"author": {
|
||||
"@type": "Person",
|
||||
"@id": "https://example.com/about#author-jane",
|
||||
"name": "Jane Doe",
|
||||
"url": "https://example.com/authors/jane-doe",
|
||||
"image": "https://example.com/images/jane-doe.jpg",
|
||||
"jobTitle": "Senior Plumber",
|
||||
"description": "Master plumber with 15 years of experience in Paris region.",
|
||||
"knowsAbout": ["plumbing", "boiler repair", "leak detection"],
|
||||
"alumniOf": "Lycée Professionnel Diderot",
|
||||
"award": ["Qualibat RGE certification", "Artisan de l'année 2024 Essonne"],
|
||||
"worksFor": {
|
||||
"@type": "Organization",
|
||||
"@id": "https://example.com/#org"
|
||||
},
|
||||
"sameAs": [
|
||||
"https://www.linkedin.com/in/jane-doe-plomberie",
|
||||
"https://twitter.com/janedoeplumbing",
|
||||
"https://www.wikidata.org/wiki/Q123456789"
|
||||
]
|
||||
},
|
||||
"publisher": {
|
||||
"@type": "Organization",
|
||||
"@id": "https://example.com/#org",
|
||||
"name": "Business Name",
|
||||
"logo": {
|
||||
"@type": "ImageObject",
|
||||
"url": "https://example.com/logo.png"
|
||||
}
|
||||
},
|
||||
"mainEntityOfPage": {
|
||||
"@type": "WebPage",
|
||||
"@id": "https://example.com/article-slug"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## TIER 2 — solid GEO contribution
|
||||
|
||||
### HowTo — procedural content
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "HowTo",
|
||||
"name": "How to reset a Chaffoteaux Talia Green boiler",
|
||||
"description": "Step-by-step reset procedure for the Talia Green combi boiler.",
|
||||
"totalTime": "PT5M",
|
||||
"estimatedCost": {"@type": "MonetaryAmount", "currency": "EUR", "value": "0"},
|
||||
"tool": [{"@type": "HowToTool", "name": "None"}],
|
||||
"step": [
|
||||
{
|
||||
"@type": "HowToStep",
|
||||
"name": "Locate the reset button",
|
||||
"text": "The reset button is on the front panel, marked with a flame icon.",
|
||||
"url": "https://example.com/guides/reset#step1",
|
||||
"image": "https://example.com/img/step1.jpg"
|
||||
},
|
||||
{
|
||||
"@type": "HowToStep",
|
||||
"name": "Press and hold for 3 seconds",
|
||||
"text": "Press the reset button until the red light turns off.",
|
||||
"url": "https://example.com/guides/reset#step2"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### BreadcrumbList — navigation context for AI
|
||||
|
||||
Gives AI the hierarchical position of the page. Nearly universal to
|
||||
add, low cost.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "BreadcrumbList",
|
||||
"itemListElement": [
|
||||
{"@type": "ListItem", "position": 1, "name": "Accueil", "item": "https://example.com/"},
|
||||
{"@type": "ListItem", "position": 2, "name": "Services", "item": "https://example.com/services"},
|
||||
{"@type": "ListItem", "position": 3, "name": "Dépannage chaudière", "item": "https://example.com/services/depannage-chaudiere"}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### LocalBusiness — local services (required for local SEO)
|
||||
|
||||
Must be consistent with GMB. Any divergence is a NAP inconsistency.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "Plumber",
|
||||
"@id": "https://example.com/#business",
|
||||
"name": "Plomberie Dupont",
|
||||
"image": "https://example.com/img/shopfront.jpg",
|
||||
"url": "https://example.com",
|
||||
"telephone": "+33123456789",
|
||||
"priceRange": "€€",
|
||||
"address": {
|
||||
"@type": "PostalAddress",
|
||||
"streetAddress": "12 rue des Lilas",
|
||||
"addressLocality": "Évry-Courcouronnes",
|
||||
"postalCode": "91000",
|
||||
"addressRegion": "Île-de-France",
|
||||
"addressCountry": "FR"
|
||||
},
|
||||
"geo": {
|
||||
"@type": "GeoCoordinates",
|
||||
"latitude": 48.62939,
|
||||
"longitude": 2.44199
|
||||
},
|
||||
"openingHoursSpecification": [
|
||||
{
|
||||
"@type": "OpeningHoursSpecification",
|
||||
"dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
|
||||
"opens": "08:00",
|
||||
"closes": "18:00"
|
||||
}
|
||||
],
|
||||
"areaServed": [
|
||||
{"@type": "City", "name": "Évry-Courcouronnes"},
|
||||
{"@type": "City", "name": "Corbeil-Essonnes"},
|
||||
{"@type": "AdministrativeArea", "name": "Essonne"}
|
||||
],
|
||||
"sameAs": [
|
||||
"https://www.facebook.com/plomberiedupont",
|
||||
"https://www.instagram.com/plomberiedupont",
|
||||
"https://www.pagesjaunes.fr/pros/12345",
|
||||
"https://www.wikidata.org/wiki/Q999999999"
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
Use the most specific subclass of `LocalBusiness` available (`Plumber`,
|
||||
`Dentist`, `Restaurant`, `AutoRepair`, etc.) — list at
|
||||
https://schema.org/LocalBusiness under "More specific Types".
|
||||
|
||||
### Organization — company-level entity
|
||||
|
||||
Separate from `LocalBusiness` when brand > single location.
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "Organization",
|
||||
"@id": "https://example.com/#org",
|
||||
"name": "Company Name",
|
||||
"legalName": "Company Name SAS",
|
||||
"url": "https://example.com",
|
||||
"logo": "https://example.com/logo.png",
|
||||
"foundingDate": "2015-03-01",
|
||||
"founders": [{"@type": "Person", "name": "Founder Name"}],
|
||||
"numberOfEmployees": {"@type": "QuantitativeValue", "value": "12"},
|
||||
"vatID": "FR12345678901",
|
||||
"iso6523Code": "0199:123456789",
|
||||
"sameAs": [
|
||||
"https://www.wikidata.org/wiki/Q123456",
|
||||
"https://www.linkedin.com/company/companyname",
|
||||
"https://www.crunchbase.com/organization/companyname"
|
||||
],
|
||||
"contactPoint": {
|
||||
"@type": "ContactPoint",
|
||||
"telephone": "+33123456789",
|
||||
"contactType": "customer service",
|
||||
"availableLanguage": ["fr", "en"]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Dataset — factual reference content
|
||||
|
||||
Use for data-heavy pages (statistics, research, public-data reports).
|
||||
|
||||
```json
|
||||
{
|
||||
"@context": "https://schema.org",
|
||||
"@type": "Dataset",
|
||||
"name": "French boiler energy consumption by model, 2020-2025",
|
||||
"description": "Average annual kWh consumption for 47 boiler models installed in France.",
|
||||
"license": "https://creativecommons.org/licenses/by/4.0/",
|
||||
"creator": {"@type": "Organization", "@id": "https://example.com/#org"},
|
||||
"distribution": {
|
||||
"@type": "DataDownload",
|
||||
"encodingFormat": "text/csv",
|
||||
"contentUrl": "https://example.com/data/boilers-2020-2025.csv"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## TIER 3 — niche but high-leverage when applicable
|
||||
|
||||
- **`Product`** — e-commerce (required for Merchant Center)
|
||||
- **`Recipe`** — food sites
|
||||
- **`Event`** — event listings
|
||||
- **`JobPosting`** — job boards
|
||||
- **`Review` / `AggregateRating`** — only when backed by verifiable public reviews (fraud risk otherwise)
|
||||
- **`VideoObject`** — any embedded video (transcripts are critical for AI)
|
||||
- **`DefinedTerm` / `DefinedTermSet`** — glossary pages, taxonomy (great for entity disambiguation)
|
||||
- **`Course` / `EducationalOccupationalCredential`** — training/cert providers
|
||||
- **`MedicalBusiness`, `PhysiologicalFeature`, `Drug`** — health (YMYL, demand extra rigour)
|
||||
|
||||
## Graph linking — @id patterns
|
||||
|
||||
Use `@id` to build a single graph across multiple JSON-LD blocks:
|
||||
|
||||
```json
|
||||
{"@context":"https://schema.org","@graph":[
|
||||
{"@type":"Organization","@id":"https://example.com/#org","name":"..."},
|
||||
{"@type":"WebSite","@id":"https://example.com/#website","publisher":{"@id":"https://example.com/#org"}},
|
||||
{"@type":"WebPage","@id":"https://example.com/page#webpage","isPartOf":{"@id":"https://example.com/#website"}},
|
||||
{"@type":"Article","mainEntityOfPage":{"@id":"https://example.com/page#webpage"},"author":{"@id":"https://example.com/about#author-jane"}}
|
||||
]}
|
||||
```
|
||||
|
||||
This is the pattern Yoast, RankMath, and modern headless-CMS plugins
|
||||
output. It lets AI engines traverse entities without duplicating them.
|
||||
|
||||
## Validation
|
||||
|
||||
- https://validator.schema.org — strict Schema.org validator
|
||||
- https://search.google.com/test/rich-results — Google Rich Results Test
|
||||
- https://developers.google.com/search/docs/appearance/structured-data — type-by-type Google docs
|
||||
@@ -0,0 +1,153 @@
|
||||
# llms.txt / llms-full.txt — template and strategy
|
||||
|
||||
## Status as of 2026-04
|
||||
|
||||
**Honest assessment**: llms.txt is a proposed standard by Jeremy Howard
|
||||
(Answer.AI, Sept 2024). No major AI crawler has publicly confirmed they
|
||||
extract content via `/llms.txt`. A Search Engine Land study (2025) found
|
||||
8 of 9 sites saw no measurable traffic change after adoption.
|
||||
|
||||
**Why include it anyway**:
|
||||
- Low cost (small static file).
|
||||
- Real value for developer-facing sites — AI coding assistants (Cursor,
|
||||
Continue, Claude Code, GitHub Copilot Chat) DO read it for doc retrieval.
|
||||
- Signals intent to AI ecosystem. Early mover advantage if adoption grows.
|
||||
- Reduces RAG token consumption when third parties ingest your content.
|
||||
|
||||
**Do not promise ranking gains.** Frame as "no-regret hedge", not "quick win".
|
||||
|
||||
## Where it goes
|
||||
|
||||
- `/llms.txt` — root of domain. Index of your content in markdown.
|
||||
- `/llms-full.txt` — root of domain. Full text of your most important pages
|
||||
concatenated. Optional but recommended for docs/blog/knowledge base.
|
||||
|
||||
Both MUST be reachable over HTTPS, content-type `text/plain` or
|
||||
`text/markdown`, and NOT blocked in robots.txt.
|
||||
|
||||
## Canonical structure
|
||||
|
||||
```markdown
|
||||
# <Site or Project Name>
|
||||
|
||||
> <One-sentence elevator pitch. This is the single line AI systems extract
|
||||
> as your site summary. Be concrete. Include entity + category + differentiator.>
|
||||
|
||||
<Optional free-form paragraph providing more context. Keep under 400 chars.>
|
||||
|
||||
## Docs
|
||||
|
||||
- [Getting started](https://example.com/docs/getting-started): What it does, how to install.
|
||||
- [API reference](https://example.com/docs/api): All endpoints with examples.
|
||||
- [Tutorials](https://example.com/docs/tutorials): Step-by-step walkthroughs.
|
||||
|
||||
## Examples
|
||||
|
||||
- [Quickstart example](https://example.com/examples/quickstart.md): Minimal working demo.
|
||||
|
||||
## Optional
|
||||
|
||||
- [Changelog](https://example.com/changelog.md): Version history.
|
||||
- [Blog](https://example.com/blog/index.md): In-depth articles.
|
||||
```
|
||||
|
||||
## Structure rules (Jeremy Howard spec)
|
||||
|
||||
1. First line: `# <Name>` (H1 with project/site name).
|
||||
2. Second non-comment line: `> summary` (blockquote, one sentence).
|
||||
3. Optional paragraphs of free-form context after the blockquote.
|
||||
4. H2 sections grouping links: `## Docs`, `## Examples`, `## Optional`, etc.
|
||||
5. Each link: `[Title](URL): description.` — description under 120 chars.
|
||||
6. Any link pointing to a `.md` version of the page is preferred.
|
||||
7. Total file: target under 8 KB. If larger, split into `llms-full.txt`.
|
||||
|
||||
## llms-full.txt
|
||||
|
||||
Concatenation of the full text (stripped of nav/footer/ads) of your most
|
||||
important pages. Separator between pages:
|
||||
|
||||
```
|
||||
---
|
||||
URL: https://example.com/docs/getting-started
|
||||
Title: Getting Started
|
||||
---
|
||||
<full markdown content of that page>
|
||||
|
||||
---
|
||||
URL: https://example.com/docs/api
|
||||
Title: API Reference
|
||||
---
|
||||
<full markdown content of that page>
|
||||
```
|
||||
|
||||
Target under 500 KB. If your corpus is larger, trim to highest-value pages
|
||||
(most-linked, most-traffic, most-updated).
|
||||
|
||||
## Generation patterns
|
||||
|
||||
### Static sites (Astro, Hugo, Jekyll, 11ty, Next.js SSG)
|
||||
|
||||
Best practice: generate both files at build time from the same source as
|
||||
your regular pages. Examples:
|
||||
|
||||
**Astro**: add a `src/pages/llms.txt.ts` endpoint:
|
||||
```typescript
|
||||
import { getCollection } from 'astro:content';
|
||||
|
||||
export async function GET() {
|
||||
const docs = await getCollection('docs');
|
||||
const body = [
|
||||
'# My Project',
|
||||
'',
|
||||
'> One-sentence pitch.',
|
||||
'',
|
||||
'## Docs',
|
||||
...docs.map(d => `- [${d.data.title}](https://example.com/docs/${d.slug}): ${d.data.description}`),
|
||||
].join('\n');
|
||||
return new Response(body, { headers: { 'Content-Type': 'text/plain' } });
|
||||
}
|
||||
```
|
||||
|
||||
**Next.js App Router**: `app/llms.txt/route.ts`:
|
||||
```typescript
|
||||
export async function GET() {
|
||||
// similar — pull from your CMS/MDX/db
|
||||
return new Response(body, { headers: { 'Content-Type': 'text/plain' } });
|
||||
}
|
||||
```
|
||||
|
||||
**Hugo**: custom output format `llms` → `llms.txt` template in layouts.
|
||||
|
||||
### CMS (WordPress, Drupal, Ghost)
|
||||
|
||||
Use a plugin OR a cron job that regenerates files weekly. Flag stale
|
||||
files (older than site content) in audits.
|
||||
|
||||
### Static HTML / PHP
|
||||
|
||||
Hand-maintained file. Flag in audits if older than 90 days.
|
||||
|
||||
## Automation tools (for SEO.md §11 "automatisation possible")
|
||||
|
||||
- **`llms-txt-action`** (GitHub Action) — generates on each deploy
|
||||
- **Mintlify** — auto-generates for Mintlify-hosted docs
|
||||
- **Fern** — auto-generates for Fern-generated API docs
|
||||
- **`llmstxt-hub`** — community directory of examples
|
||||
- Custom script + cron — works for any static content source
|
||||
|
||||
## What NOT to put in llms.txt
|
||||
|
||||
- Login walls / private content
|
||||
- Pricing tables (change frequently → stale risk)
|
||||
- Testimonials (authenticity risk if AI quotes them)
|
||||
- Marketing fluff without factual anchors
|
||||
|
||||
## Validation checklist
|
||||
|
||||
- [ ] File reachable at `/llms.txt` over HTTPS
|
||||
- [ ] Content-type `text/plain` or `text/markdown`
|
||||
- [ ] H1 + blockquote present as first two non-comment lines
|
||||
- [ ] All linked URLs resolve (200)
|
||||
- [ ] No broken markdown (valid CommonMark)
|
||||
- [ ] Mentioned in `/sitemap.xml`? Optional, debated
|
||||
- [ ] NOT blocked in `/robots.txt`
|
||||
Reference in New Issue
Block a user