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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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
# <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)
- First line:
# <Name>(H1 with project/site name). - Second non-comment line:
> summary(blockquote, one sentence). - Optional paragraphs of free-form context after the blockquote.
- H2 sections grouping links:
## Docs,## Examples,## Optional, etc. - Each link:
[Title](URL): description.— description under 120 chars. - Any link pointing to a
.mdversion of the page is preferred. - 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:
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:
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.txtover HTTPS - Content-type
text/plainortext/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