agentleFS
Kevin-Liu-01Kevin-Liu-01/Claude-of-Tanks/api/SKILL.md

api-skill

Skill531 starsChanged 3 months agoMITView on GitHub

Maintain the telemetry, Jev proxy and public GitHub-count HTTP entrypoints.

  • Reads credentials

2 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions2 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 2

    1. JustSteveKing/api-skill★ 82same name
    2. techhorizonlabs/gearlist★ 2same 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 repository9 other files it gives its agents.

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
  • could be automatic: a setting could enforce it
  1. Very specific:

    Keep responses that could carry a credential private/no-store.

    line 48

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

claude-of-tanks / api

Purpose

<!-- agent-docs:fill:purpose -->

Expose the hosted application's small server-side API surface. Keep deployment adapters thin; room policy belongs to src/mp/room and server/, not browser code.

Mental model & key files

<!-- agent-docs:fill:model -->

Relay credentials are minted inside the room for its seated players (server/relayCredentials.ts, the rooms Worker's room_relay); no route here answers ICE servers (docs/MULTIPLAYER-V2.md §13.14). github-stars.ts logs cot-github-stars lines per upstream failure. github-stars.ts proxies the public repository count with bounded upstream requests and cache headers. telemetry.ts is the entry-telemetry fallback sink (docs/ENTRY-RESILIENCE.md), used only while VITE_TELEMETRY_URL is unset: one v2 record per request validated through the shared schema server/telemetryRecord.ts (personal field names refused), one log line per record, no store. The production sink is the Cloudflare Worker cloudflare/telemetry (Workers Analytics Engine). rooms-status.ts (2026-10-23, the Workers Free ruling) reads the rooms Worker's /healthz from the server and answers { state: 'ok' | 'limited' | 'unavailable' }. It names Cloudflare's daily-limit refusal (error 1027, a 429), which a browser cannot read from a failed WebSocket upgrade. It is cached at the edge, and the Play menu asks it once after a failed or interrupted room (src/mp/session/roomServiceLimit.ts). jev.ts is the Jev commander proxy (docs/JEV-COMMANDER.md): one text-only team document per request, validated and bounded, the TypeSafe questions built server-side, the server-held TYPESAFE_API_KEY never leaving the function, upstream 401/422/429/529/timeouts mapped to clean errors with a cool-down, per-address and per-session buckets, a session budget and a global ceiling. Deployment routes are configured in vercel.json. The signaling function of the first multiplayer (api/signal.ts) left the tree with the cutover of 2026-09-29 (docs/MULTIPLAYER-V2.md §13.10): rooms live in the cloudflare/rooms Worker.

Patterns to follow / invariants

<!-- agent-docs:fill:patterns -->
  • Preserve allowed-origin checks, method/status contracts, and upstream timeouts.
  • Origins, the canonical host and the Worker URLs come from the deployment policy module api/_lib/policy.ts (allowedApiOrigins(env)); never repeat them in a function. _-prefixed paths are shared code, not routes. The Workers' ALLOWED_ORIGINS and the entry telemetry literals are pinned to it by node tools/deployment-policy.selftest.mjs.
  • Keep responses that could carry a credential private/no-store; relay credentials belong to the room (server/relayCredentials.ts), never to a public route. Document environment variable names only; never commit secret values or log credentials.
  • Handler factories accept injected fetch, clock, and environment dependencies so failure paths can be tested without external services.

Common tasks → first action

<!-- agent-docs:fill:tasks -->
  • TURN configuration: the room's issuer, server/relayCredentials.ts (node server/relayCredentials.selftest.mjs; the Worker's npm --prefix cloudflare/rooms test).
  • Star-count responses: run node server/githubStars.selftest.mjs; inspect src/ui/githubStars.ts for the loading/error presentation contract.
  • Telemetry beacon: run node server/telemetryRecord.selftest.mjs, node server/telemetry.selftest.mjs and node src/entry/telemetry.selftest.mjs; the Worker sink is npm run test:telemetry:cloudflare; read the funnel with node tools/telemetry-report.mjs (docs/ENTRY-RESILIENCE.md, cloudflare/telemetry/README.md).
  • Jev commander proxy: run node server/jev.selftest.mjs (fake upstream: auth header, server-built questions, every error mapping, rate limits, budget, origin and state validation); locally npm run jev:dev serves it on 8794 with the key from the environment (docs/JEV-COMMANDER.md).

Gotchas

<!-- agent-docs:fill:gotchas -->

TURN credentials and a public count have different caching requirements. Do not import a function module into client bundles.

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.