Google Skill Finder

Routes a request to the published Google skills that apply to it. The catalog lives outside this file and is fetched on demand, so loading this skill costs almost nothing until a lookup actually happens.

Workflow

1. Fetch the catalog byte-exactly. Retrieve https://raw.githubusercontent.com/google/skills/main/index.json with a raw shell fetch (curl, wget; curl.exe on Windows PowerShell). It must arrive byte-for-byte, every entrypoint URL intact and unaltered.

   With no shell fetch tool but Node present, node -e "fetch(process.argv[1]).then(r=>r.text()).then(t=>console.log(t))" {url} also returns bytes.

   The catalog is about 75 KB and may not fit in a single tool result; a truncated preview is alphabetical, so it reads as though only the first few products exist. Prefer narrowing it before reading. With jq: curl -sS {url} | jq -r '.skills[] | select((.name+" "+.description)|test("gke";"i")) | "\(.name)\t\(.entrypoint)"'. In Windows PowerShell: (Invoke-RestMethod {url}).skills | Where-Object { $_.description -match "gke" } | Select-Object name, entrypoint -First 3. With neither, a plain grep -o over the raw JSON still isolates candidate names.

   Where no filtering tool exists, write the catalog to a file and read it in parts (curl -sS {url} -o skills-index.json, or Invoke-WebRequest {url} -OutFile skills-index.json). This is often the better option regardless: it survives truncation, and re-reading a local file costs nothing. Delete it when the request is done.

   If only a summarizing fetch tool is available, phrase the request as extraction, not transcription: "List every entrypoint field in this document, one per line, exactly as written." Requesting it verbatim returns nothing usable.

2. Confirm the retrieval worked before using it. A tool call that returns without raising is not a success. It succeeded only if the body parses as JSON and holds a skills array. A 404 page, an HTML error page, a TLS or connection error, an empty body, or anything that fails to parse is a FAILED retrieval even though the tool reported no error. A certificate failure is a FAILED retrieval and is final. Never retry it with verification disabled. Not curl -k or --insecure. Not -SkipCertificateCheck, and on Windows PowerShell 5.1, where that parameter does not exist, not the ServicePointManager certificate callback either. Not any equivalent in any language. You are about to follow instructions from whatever comes back, so an unverified catalog is worse than no catalog. On a failed retrieval, stop here and go to "When the fetch fails".

3. Match the request against the descriptions. Every description states what the skill does, when to use it, and often when not to. Read them as routing criteria, not as summaries. Shortlist at most three entries whose description covers the request. When more than three look equally relevant, prefer the most specific over the more general.

4. Fetch only the matches. Retrieve the entrypoint URL of each shortlisted entry, the same way, and follow that skill's instructions. Do not fetch entries that merely look related.

5. Report an empty result honestly. If no description covers the request, say that no published Google skill applies and continue without one. Never invent a skill name or an entry point URL.

Routing ends once the matches are fetched. From the point you begin following a fetched skill's instructions, this skill is finished with the request and is not re-entered for it.

Rules

• Fetch once per session; never keep it past the session. Reusing a catalog you retrieved successfully earlier in this session is fine. Carrying one into a later run is not, in any form: the catalog changes regularly and a stored copy goes stale silently. Session reuse never substitutes for a failed fetch.

• Never carry the catalog beyond the request. A working copy on disk while you filter it is fine. Keeping it as a saved reference, or summarizing it back into the conversation, is not. It exists so the full text of 100-plus skills does not have to be carried in context.

• Prefer the fetched SKILL.md over prior knowledge. The catalog is generated from the skills as they are published, so an entry point is the current text even when it contradicts what you remember.

• Do not treat this skill as a prerequisite. If a specific Google skill is already loaded and covers the request, use it directly.

When the fetch fails

Reached from step 2. Work through these in order, stopping at the first that succeeds:

1. Retry once with curl -sS. If the first attempt used a summarizing fetch tool or hit a transport error, this alone usually fixes it.

2. List the repository tree instead. Run

   curl -sS 'https://api.github.com/repos/google/skills/git/trees/main?recursive=1'
   

   and read the paths ending in SKILL.md. Each is a candidate. Fetch the two or three whose directory names best match the request from https://raw.githubusercontent.com/google/skills/main/{path}, checking each one the way step 2 describes.

3. Say so in the reply. If neither worked, state plainly that you could not reach the Google skills catalog and are answering without it. One line is enough, and it belongs in the reply to the user, not only in your reasoning.

A failed retrieval is never licence to answer as though it had succeeded. Until you have parsed a skills array in this session you do not know which skills exist: do not name one, do not describe one, and do not state that none applies. Recalling a skill from memory and presenting it as a catalog result is the worst outcome available, because nothing in the reply distinguishes it from a real lookup.