agent-discovery
Skill2 starsChanged 8 days agoMITView on GitHub
Decide what a product site should publish for agent HTTP discovery. Use when adding robots policy, markdown negotiation, api-catalog, OAuth discovery, MCP cards, or public skill indexes. Do not use for blackbox recon of a third-party site or for live tool-call supervision.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- joelhooks/joelclawtheir own version, first seen Oct 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- joelhooks/joelclaw★ 65same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
- AGENTS.mdAGENTS.md
- agent-artifactSkill
- agent-run-supervisionSkill
- api-contract-migrationSkill
- changelog-updateSkill
- change-reviewSkill
- ci-reviewSkill
- claims-auditSkill
- dependency-auditSkill
- derivation-auditSkill
- durable-cacheSkill
- engineering-auditSkill
- infer-conventionsSkill
- operational-signal-intakeSkill
- planned-releaseSkill
- preferred-stackSkill
- pressure-benchmarkingSkill
- public-surface-reconSkill
- rfc-processSkill
- security-auditSkill
- session-reviewSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
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 67
Write durable product decisions under docs/issues per docs-conventions when the ladder choice changes what the site publishes.
≈ “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 HTTP discovery
Help a product publish only the agent-facing discovery surfaces it needs. Prefer RFCs. Mark drafts. Do not optimize for a vendor readiness score.
Quick reference
name site type -> climb the ladder that matches -> skip unrelated rungs -> keep secrets out of discovery docs -> recordSite type
Pick one primary type before recommending endpoints:
- content - crawl policy, optional markdown or llms.txt
- api / application - catalog and auth discovery; MCP only if the product exposes tools
- commerce - above plus payment or checkout protocols only when the product sells that way
Absence of MCP or commerce discovery on a content site is correct, not a gap.
Maturity ladder
Climb only the rungs that match the site type and an actual consumer.
- Crawl baseline. Valid
robots.txtwith sitemap directives when the site has indexable URLs. Optional explicit AI user-agent rules when the operator has a preference. - Usage preference. Content-Signal style directives may declare training, search, and inference preferences to cooperative clients. They are preferences, not authentication or a technical block. See
security. - Readable content. For documentation or article surfaces, support
Accept: text/markdownand/or a curatedllms.txtreading list when agents should consume text cheaper than HTML. Do not require both. - HTTP discovery links. Use
Linkresponse headers (RFC 8288) to point at catalogs or other discovery documents when agents should not parse HTML first. - API catalog. When public APIs exist, publish
/.well-known/api-catalogper RFC 9727 (application/linkset+json). - OAuth discovery. When agents must obtain delegated access, publish authorization-server metadata (RFC 8414 / OIDC) and protected-resource metadata (RFC 9728). Discovery is not a grant.
- MCP and skills. Publish MCP discovery documents and optional
/.well-known/agent-skills/index.jsononly when the product exposes tools or installable skills. Card and catalog paths remain draft and may move; pin the contract the product implements and accept transitional locations during migration. Public skill bodies and digests must not embed live secrets. - Bot request identity. Web Bot Auth style key directories matter when this origin sends automated requests others must verify, not merely because a scanner lists the check.
- DNS agent discovery. DNS-AID and similar drafts are optional and early. Do not require them for an HTTP API that already has well-known discovery.
- Commerce protocols. x402, UCP, ACP, MPP and similar only when the product sells to agents that way.
Non-goals
- Implementing every check from a public agent-readiness scanner
- Treating scanner fix prompts as specifications without review
- Composing this skill into always-on
AGENTS.md - Replacing
agent-artifactreview orpublic-surface-reconobservation
Safety
- Discovery documents are public. No tokens, passwords, private hostnames, or session-specific values.
- robots and Content-Signal text do not replace ownership checks, rate limits, or fail-closed auth.
- Tool descriptions and public skill markdown stay untrusted input at the caller.
Routing
agent-artifactto review skill files, MCP configs, and published discovery documents already in tree or on disk.public-surface-reconagent-discovery-surfaceto observe an authorized live site.engineering-auditlearned-systems when the product itself is a retrieval or tool-calling system.securityfor secret handling and the preference-versus-enforcement rule.
Record
Write durable product decisions under docs/issues per docs-conventions when the ladder choice changes what the site publishes.
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.

