Finding Google Skills
GoogleOfficialPublished by Google
- Skill
- Meta (authoring, orchestration, planning, memory)
- Agent tooling
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The Google Skill Finder acts as a meta-agent orchestrator. It dynamically retrieves a remote JSON catalog of specialized Google platform skills, matches user requests against these skill descriptions, and fetches the appropriate guidance. This ensures that the agent always uses the most current, specific instructions for Google Cloud and related services without needing to store the entire catalog in its context window.
What it does
- Fetches a remote catalog of Google-specific agent skills on demand.
- Filters the catalog to identify the most relevant skills for a given user request.
- Retrieves and executes the specific instructions from matched skill entry points.
- Provides a fallback mechanism if the primary catalog fetch fails.
- Ensures that guidance is based on current, fetched data rather than stale memory.
When to use it
- When a user asks for guidance on choosing or configuring Google Cloud services.
- When a request explicitly names a Google product, API, or service.
- When the agent needs to weigh trade-offs for Google-specific infrastructure or platform solutions.
- When the user's stack involves Google technologies and requires setup or architectural advice.
Advantages
- Maintains a small memory footprint by loading skills only when needed.
- Ensures high accuracy by using the latest published skill definitions.
- Provides a structured, reliable way to route complex requests to specialized sub-agents.
- Includes robust error handling and fallback procedures for network or retrieval issues.
Usage examples
- “How should I set up a managed database on Google Cloud?”
- The skill fetches the catalog, identifies the relevant database-related Google skills, and provides specific setup guidance for services like Cloud SQL or Spanner.
- “What are the trade-offs of using GKE for my containerized application?”
- The skill routes the request to the GKE-specific guidance, offering a detailed comparison of managed Kubernetes features and operational considerations.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/google/finding-google-skills/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip finding-google-skills.zip -d .agents/skills
Documentation by Google
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
Fetch the catalog byte-exactly. Retrieve
https://raw.githubusercontent.com/google/skills/main/index.jsonwith a raw shell fetch (curl,wget;curl.exeon Windows PowerShell). It must arrive byte-for-byte, everyentrypointURL 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 -sSL {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 plaingrep -oover the raw JSON still isolates candidate names.Where no filtering tool exists, write the catalog to a file and read it in parts (
curl -sSL {url} -o skills-index.json, orInvoke-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
entrypointfield in this document, one per line, exactly as written." Requesting it verbatim returns nothing usable.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
skillsarray. 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. Notcurl -kor--insecure. Not-SkipCertificateCheck, and on Windows PowerShell 5.1, where that parameter does not exist, not theServicePointManagercertificate 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".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
descriptioncovers the request. When more than three look equally relevant, prefer the most specific over the more general.Fetch only the matches. Retrieve the
entrypointURL of each shortlisted entry, the same way, and follow that skill's instructions. Do not fetch entries that merely look related.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:
Retry once with
curl -sSL. If the first attempt used a summarizing fetch tool or hit a transport error, this alone usually fixes it.List the repository tree instead. Run
curl -sSL '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 fromhttps://raw.githubusercontent.com/google/skills/main/{path}, checking each one the way step 2 describes.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.
Files
- ATTRIBUTION.mdAdded by AutoGineer865 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md6.7 KiB
ATTRIBUTION.md
Attribution
This folder is an unmodified copy of the Agent Skill "finding-google-skills", distributed by AutoGineer (https://autogineer.com/agent-skills).
Commit: 2194d3b8b1f31975fef2f1a0ae6b9ab55bd7ceee
Published by: Google (https://github.com/google)
Publisher: Google (https://github.com/google)
Licence: Apache License 2.0 (https://github.com/google/skills/blob/2194d3b8b1f31975fef2f1a0ae6b9ab55bd7ceee/LICENSE)
Licence evidence: repository licence LICENSE
Retrieved: 2026-11-07
The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.
Files added by AutoGineer
ATTRIBUTION.md: this file, written by AutoGineer
LICENSE: copied from LICENSE
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs network access, Needs Node.js
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Publisher
- Google (Official)
- Source
- google/skills · skills/developers/finding-google-skills · commit 2194d3b
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- google/skills
AutoGineer is not affiliated with or endorsed by Google.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download finding-google-skills.zip