SageMaker Serving Image Selection
huggingface/skills
Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.
Google platform decision and setup guidance, loaded on demand from Google's skill catalog.
$ npx skills add google/skills --skill finding-google-skills -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google/skills finding-google-skills --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/developers/finding-google-skills .claude/skills/finding-google-skills && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .claude/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google/skills/tree/main/skills/developers/finding-google-skillsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google/skills --skill finding-google-skills -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google/skills finding-google-skills --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/developers/finding-google-skills .agents/skills/finding-google-skills && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .agents/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill finding-google-skills -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google/skills finding-google-skills --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/developers/finding-google-skills .cursor/skills/finding-google-skills && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .cursor/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google/skills.git --path skills/developers/finding-google-skills--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google/skills --skill finding-google-skills -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google/skills finding-google-skills --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/developers/finding-google-skills .gemini/skills/finding-google-skills && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .gemini/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google/skills finding-google-skillsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google/skills --skill finding-google-skills -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/developers/finding-google-skills .github/skills/finding-google-skills && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .github/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill finding-google-skills -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google/skills finding-google-skills --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/developers/finding-google-skills .opencode/skills/finding-google-skills && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "finding-google-skills" agent skill from https://github.com/google/skills/tree/main/skills/developers/finding-google-skills into .opencode/skills/finding-google-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-google-skills", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
finding-google-skillsGoogle platform decision and setup guidance, loaded on demand from Google's skill catalog.
Finding Google Skills is an agent skill from google/skills, published by the product's own GitHub organization. Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they…
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering LLM inference and serving. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 5120a76. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curljqFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
api.github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Finding Google Skills loads about 1.7k tokens when it runs. Until then it costs about 173 tokens; SKILL.md has 895 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from google/skills at commit 5120a76, republished under its Apache-2.0 licence (© google). 895 words, ~1,711 tokens.
.claude/skills/finding-google-skills/SKILL.md (or your agent's skills folder).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.
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 -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 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 -sSL {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.
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".
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.
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.
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.
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.
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 from
https://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.
© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/developers/finding-google-skills of google/skills.
Open the folder on GitHubat commit 5120a76
Finding Google Skills next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Finding Google Skills this skillgoogle/skills | 21k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| SageMaker Serving Image Selectionhuggingface/skills | 11k | 1 repos | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Qwen Mtp GgufR6410418/Jackrong-llm-finetuning-guide | 1.7k | — | ~1.7k | Automated safety check: Pass | MIT | |
| CI Fails Buildkiteguqiong96/Lvllm | 465 | 2 repos | ~349 | Automated safety check: Pass | Apache-2.0 | |
| Subwave LLM Benchperminder-klair/subwave | 1.4k | — | ~2.4k | Automated safety check: Notes | MIT |
huggingface/skills
Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.
huggingface/skills
Runs evaluations of Hugging Face Hub models on local hardware with inspect-ai or lighteval, and helps choose between vLLM, Transformers and accelerate backends.
R6410418/Jackrong-llm-finetuning-guide
Complete agent-ready workflow for Qwen-family MTP or nextn GGUF conversion and release.
guqiong96/Lvllm
Fetch and diagnose vLLM Buildkite CI failure logs. An agent skill from guqiong96/Lvllm.
perminder-klair/subwave
Benchmark and compare LLM models for SUB/WAVE's on-air calls — track picks, segments, listener requests, DJ scripts, banter, and programme beats — in both candidate-pool and agent modes, using…
intel/auto-round
Adapt AutoRound to support a new diffusion model architecture (DiT, UNet, hybrid AR+DiT).
google/skills
Query Cloud Trace spans, filter by latency thresholds or error status, correlate distributed traces with Cloud Logging, and diagnose latency bottlenecks across Google Cloud services.
google/skills
Manages Google Cloud Privileged Access Manager entitlements and grants: create and edit entitlements, request temporary access, and approve or deny pending grants.
google/skills
Writes Terraform alerting policies for AI agents that emit OpenTelemetry metrics, covering reliability, cost, safety, security and quality signals on Google Cloud.
google/skills
Deploys open models or custom weights from Model Garden to Agent Platform endpoints, checks deployment status and cleans up endpoints, confirming before any change.
google/skills
Searches, manages and scaffolds skills in the Gemini Enterprise Agent Platform Skill Registry using bundled Python scripts and Google Cloud credentials.
google/skills
Designs GCP infrastructure as local Terraform, validates and scans it against best practices, then imports it to Application Design Center for deployment and troubleshooting.
Categories
Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Finding Google Skills is an agent skill from google/skills, published by the product's own GitHub organization. Google platform decision and setup guidance, loaded on demand from Google's skill catalog.
Finding Google Skills fits situations like: A developer is choosing; setting up part of their stack; such as where to run a service; AI model serving.
Run `npx skills add google/skills --skill finding-google-skills -a claude-code`. Or copy the skill folder (skills/developers/finding-google-skills in google/skills) into .claude/skills/finding-google-skills in your project. Claude Code loads it when a task matches its description.
Run `npx skills add google/skills --skill finding-google-skills -a codex`. Or copy the skill folder (skills/developers/finding-google-skills in google/skills) into .agents/skills/finding-google-skills in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill finding-google-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/finding-google-skills, .gemini/skills/finding-google-skills, .github/skills/finding-google-skills and .opencode/skills/finding-google-skills in your project.
Going by SKILL.md and its folder, Finding Google Skills needs the command-line tools its instructions call (curl and jq).
SKILL.md names 1 domain. As links in the text: api.github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Finding Google Skills is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Finding Google Skills: SageMaker Serving Image Selection (huggingface/skills, 11k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars), Qwen Mtp Gguf (R6410418/Jackrong-llm-finetuning-guide, 1.7k stars) and CI Fails Buildkite (guqiong96/Lvllm, 465 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
google (a GitHub organization, an official publisher) maintains it in google/skills, which has 21,069 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on October 9, 2026.
Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.