agent-aeo
Skill1 starsChanged 4 months agoApache-2.0View on GitHub
Implement agent-oriented website access and AI crawler discovery for public websites. Use when adding or auditing /.well-known/agent.json, llms.txt, llms-full.txt, per-page index.md, per-page llms.txt, Accept: text/markdown negotiation, ?mode=agent markdown views, canonical markdown or plain-text page extraction, or other agent-friendly content routes and headers.
In this repository19 other files it gives its agents.
- AGENTS.mdAGENTS.md
- agent-memorySkill
- beanquerySkill
- ci-repairbaySkill
- delegated-developmentSkill
- ghSkill
- issue-blueprintSkill
- issue-workbenchSkill
- minifluxSkill
- og-imageSkill
- opSkill
- pencil-to-figma-migrationSkill
- pr-comment-sweepSkill
- pr-launchpadSkill
- repo-surveyorSkill
- review-checkpointSkill
- review-repairbaySkill
- shipyardSkill
- skill-optimizerSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 20
Use one server-side resolver accepting canonical path, optional locale, and output content type.
- Distinctive: line 35
Use request-level tests for behavior, not source formatting:
- Distinctive: line 43
Run the focused route tests plus the repository's typecheck/build and lint.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent AEO
Expose public site content without scraping rendered HTML. Add only the surfaces the site needs:
/.well-known/agent.json:application/json; charset=utf-8; advertise only implemented absolute URLs or patterns, locales, and canonical origin. Keep it static when possible and never include secrets or user-specific data./llms.txtand optional/llms-full.txt:text/plain; charset=utf-8compact and expanded site maps with absolute discovery links./<path>/index.md,?mode=agent, andAccept: text/markdown:text/markdown; charset=utf-8representations of the same canonical page./<path>/llms.txt: the same page rendered as readable plain text.
Use one server-side resolver accepting canonical path, optional locale, and
output content type. Resolve existing route, Markdown, CMS, template, or static
data; render Markdown first and convert to plain text only at the response
boundary. Return 404 for unsupported paths. Page responses must include the
real body, title, canonical URL, and enough site context for a deep link;
articles must not stop at excerpts or metadata.
Route these surfaces through one dynamic handler, rewrite, proxy, or middleware
path rather than per-page files. Normalize agent suffixes and ?mode=agent
before resolution, preserve the original path when a framework rewrite loses
it, set Vary: Accept for negotiated responses, and keep root discovery routes
out of page-level catch-alls. Do not create a separate visual agent page.
Tests
Use request-level tests for behavior, not source formatting:
- advertised root routes return their declared content types;
- Markdown variants share canonical content and plain text preserves it;
- nested paths and article bodies work;
- page catch-alls do not swallow root routes;
- negotiated responses set
Vary: Accept.
Run the focused route tests plus the repository's typecheck/build and lint; smoke test representative URLs when routing changes. Missing bodies, placeholder content, or duplicated route files are defects, not warnings.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

