AI-SKILL
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Bu listing icin henuz AI raporu yok.
A curated index of 900+ agent skills across 49 categories — repos, cookbooks, MCP servers, and case studies. One YAML file, bilingual, hand-maintained.
AI-SKILL
A working index of agent skills — repos, cookbooks, MCP servers,
production case studies. The stuff you'd actually want when building
with LLMs.
Not a library. Not a tutorial site. Just a single YAML file with
900+ curated source_url pointers, sorted into 49 categories.
You read it, you click through, you use the upstream project. That
is the whole loop.
Why this exists
The agent ecosystem has thousands of good repos scattered across
GitHub, arXiv, and the corporate research blogs. Searching GitHub
directly returns noise. The existing awesome-lists are usually
abandoned or vendor-driven.
This repo is one hand-curated YAML file. The value is in the
picking: every entry has a source_url that resolves, a one-linesummary / summary_zh, and a category from a closed set of 49.
You can grep it, vendor it, render it, or clone it as a starting
point for your own list.
What's in the box
catalog/skills.yaml— the index. 1,551 entries across 49
categories, bilingual (en + zh). One entry per upstream repo.catalog/own_skills.yaml— an empty placeholder for skills
we author and host in this repo. Seeskills/for the format.skills/— drop-in folder for our own skills (frontmatter +
Markdown). Empty by design; fill it when you have something.
We don't host, mirror, or repackage anyone else's work. The catalog
points; the upstream delivers.
The 49 categories
The full list lives in catalog/skills.yaml under categories:.
A sample so you know the shape:
| # | Category | What goes here |
|---|---|---|
| 01 | Official Cookbooks | Vendor pattern books (Anthropic, OpenAI, Google, …) |
| 03 | Agent Frameworks | LangChain, AutoGen, CrewAI, smolagents, … |
| 04 | RAG & Retrieval | Vector stores, retrievers, chunkers, embedding pipelines |
| 10 | MCP Protocol | Model Context Protocol servers, clients, gateways |
| 22 | Synthetic Data | Self-instruct, evol-instruct, distillation |
| 35 | Reasoning Models | Chain-of-thought, o1-style, self-consistency |
| 49 | Case Studies | Production post-mortems, industry reports |
New entries fit into an existing category. New categories need a
reason — open an issue first if you think one is missing.
Entry schema
Each record under the top-level skills: list incatalog/skills.yaml:
- slug: anthropic-cookbook # unique id, kebab-case
title: Claude Cookbook # display name (en)
title_zh: Claude Cookbook # display name (zh)
source: anthropics/anthropic-cookbook # owner/repo on GitHub
source_url: https://github.com/anthropics/anthropic-cookbook
category: official-cookbooks # one of the 49 slugs above
subgroup: us-frontier-labs # optional, for finer grouping
tags: # 2-5 lowercase tags
- claude
- anthropic
- official
- notebook
summary: Anthropic's official notebook collection for Claude — tool use, PDF, structured output.
summary_zh: Anthropic 官方 notebook 合集:工具调用、PDF 理解、结构化输出。
stars: 22000 # refreshed daily by sync-github
license: MIT # SPDX id, refreshed daily
pushed_at: 2026-06-04 # last commit on upstream
added: 2026-06-04 # when we added it to the index
archived: false # true if upstream went read-only
source and source_url are the pointers; the rest is metadata.
The added date is when the entry landed in the index — don't
conflate it with file modification time.
For non-GitHub sources (e.g. arXiv papers, blog postmortems in the
case-studies category), the source field can be a domain likearxiv.org and the source_url the actual paper URL. The
sync-github script skips those entries automatically.
Using the catalog
The repository is the catalog. There is no docs site, no Pages
build, no API. The data is the product.
Programmatic read:
import yaml
with open("catalog/skills.yaml") as f:
data = yaml.safe_load(f)
entry = next(s for s in data["skills"] if s["slug"] == "langchain")
print(entry["source_url"])
Grep-style read with yq:
# All RAG-related entries, slug + url
yq '.skills[] | select(.category == "rag-retrieval")
| [.slug, .source_url] | @tsv' catalog/skills.yaml
# All entries from a single org
yq '.skills[] | select(.source | startswith("openai/"))
| .slug' catalog/skills.yaml
# Categories with their entry counts
yq '.skills | group_by(.category) | .[]
| {cat: .[0].category, n: length}' catalog/skills.yaml
Extending the catalog
Adding an external skill is one PR, one file edit:
- Fork the repo.
- Append a new entry under
skills:incatalog/skills.yaml
using the schema above. - Constraints:
slugunique,source_urlresolves (2xx, not 404),summaryandsummary_zheach one line,categoryfrom the
closed set of 49. - Open a PR. The link-check workflow pings your
source_url.
After merge, the sync workflow will backfillstars/license
/pushed_atwithin a day.
Publishing your own skill on the in-repo shelf:
- Copy
skills/_TEMPLATE.mdtoskills/<your-slug>.md. - Add a row to
catalog/own_skills.yamlwith at least apath
field pointing back to your file. - Open a PR.
No review queue, no formal process. If the entry is right and the
link works, it lands.
The two helper scripts
Both are in scripts/. Stdlib-only except for pyyaml andruamel.yaml. Both work locally and in CI.
scripts/sync-github.py
Refreshes stars, license, pushed_at, and archived for every
GitHub-hosted entry via the GitHub API. Runs daily at 06:00 UTC,
opens a PR with the diff.
pip install ruamel.yaml
GITHUB_TOKEN=ghp_xxx python scripts/sync-github.py --dry-run # preview
GITHUB_TOKEN=ghp_xxx python scripts/sync-github.py # apply
Without a token you get 60 req/h (sequential, ~15 h for 900
entries). With a token you get 5,000/h and 12 concurrent workers
(~3 minutes).
scripts/check-links.py
Pings every source_url, classifies the result, and writes the
summary to data/health.json. Runs weekly on Mondays at 04:00 UTC.
Fails the workflow on any 4xx/5xx/timeout, so dead links are loud.
pip install pyyaml
python scripts/check-links.py # prints summary
python scripts/check-links.py --fail # exit 1 on any broken link
If a link breaks (repo moved, went private, the URL is malformed),
the script says so and the workflow fails. You fix the URL in the
next PR and the next Monday's run goes green again.
When this isn't the right tool
- You want a deep technical comparison of two frameworks. We don't
benchmark; we point you to the upstream. - You need real-time star counts. We refresh daily; for live
numbers go to GitHub. - You're looking for tutorials. We link to the repos that contain
them.
License
MIT — see LICENSE. The catalog index is MIT-licensed.
Each linked skill keeps its upstream license.
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