Skills Library
Curated bilingual (EN + RU) skills in the universal Agent Skills format
Works with Claude Code, OpenCode, Cursor, Windsurf and every Agent Skills-compatible tool
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Install in one line
curl -fsSL https://raw.githubusercontent.com/ssrjkk/agent-skills/main/install.sh | bash
Or clone directly into your agent's skills directory:
| Agent | Command |
|---|---|
| Claude Code | git clone --depth 1 https://github.com/ssrjkk/agent-skills.git ~/.claude/skills |
| OpenCode | git clone --depth 1 https://github.com/ssrjkk/agent-skills.git ~/.opencode/skills |
| Cursor | git clone --depth 1 https://github.com/ssrjkk/agent-skills.git ~/.cursor/skills |
| Windsurf | git clone --depth 1 https://github.com/ssrjkk/agent-skills.git ~/.windsurf/skills |
What is this?
65 production-grade, bilingual (English + Russian) skills following the
universal Agent Skills format — the SKILL.md convention shared by Claude
Code, OpenCode, Cursor, Windsurf and other agents. Each skill is a folder with
a SKILL.md (primary, English) and an optional SKILL.ru.md (parallel
Russian translation). Any agent that implements the Agent Skills spec can
consume them directly.
The library ships with a Python SDK + CLI for validation, quality scoring, cataloging and search, all enforced in CI.
Quick Start
# Install the SDK + CLI from PyPI
pip install agent-skills-library
# Explore the library (both `agent-skills` and `claude-skills` work)
agent-skills stats # Library statistics
agent-skills search <query> # Search skills
agent-skills validate # Validate all skills (EN + RU)
agent-skills quality # Quality analysis
agent-skills catalog # Rebuild skills_catalog.json
Using the skills with your agent
Every skill is a standard Agent Skills directory:
.claude/skills/
{domain}/
{skill-name}/
SKILL.md <- English (primary)
SKILL.ru.md <- Russian (parallel)
To install a skill into another agent, point it at the same folder — the file format is identical, only the root directory changes:
| Agent | Default skills root | Notes |
|---|---|---|
| Claude Code | .claude/skills/ |
Native |
| OpenCode | .opencode/skills/ |
Same SKILL.md format |
| Cursor | .cursor/skills/ |
Same SKILL.md format |
| Windsurf | .windsurf/skills/ |
Same SKILL.md format |
Frontmatter is strictly validated for cross-agent portability in CI
(scripts/check_agent_interop.py): portable name, single-line
description, no duplicate names.
Stats
| Metric | Value |
|---|---|
| Total skills | 65 |
| Russian translations | 65 (100%) |
| Domains | 16 |
| Quality score | 100% (Grade A) |
| Test coverage | 100% |
| License | MIT |
Only skills meeting the quality bar (Grade A, no validation errors) are kept
in main. Everything else is archived under the v1.0-legacy tag.
Skills by domain
| Domain | Skill | Description |
|---|---|---|
ai |
few-shot-learning |
Few-shot prompt design with example selection |
ai |
llm-finetuning |
Fine-tuning LLMs end-to-end |
ai |
prompt-engineering |
Reliable prompt design for LLMs |
ai |
rag-pipeline |
Retrieval-augmented generation |
ai |
agent-development |
Reliable LLM agents with tools |
ai |
mcp-servers |
Model Context Protocol servers |
ai |
llm-evals |
Evaluation suites for LLMs |
ai |
function-calling |
Robust LLM tool calling |
ai |
prompt-caching |
LLM cost & latency optimization |
ai |
mlops |
ML in production lifecycle |
backend |
deno-runtime |
Deno realtime apps & Workers |
backend |
nestjs |
NestJS modular backends |
backend |
rust-tokio |
Async Rust with Tokio |
backend |
fastapi |
High-performance Python APIs |
backend |
go-rest-api |
REST APIs in Go |
backend |
rest-api-design |
Consistent REST API design |
backend |
django |
Secure Django web apps |
backend |
grpc |
High-performance gRPC services |
backend |
express |
Node.js APIs with Express |
blockchain |
zk-proofs |
Zero-knowledge proofs |
data |
pandas |
Tabular data analysis & ETL |
data |
sql-querying |
Correct & efficient SQL |
data |
elasticsearch |
Search & log analytics |
database |
postgresql |
PostgreSQL schema & queries |
database |
prisma-orm |
Prisma ORM data layer |
database |
redis |
Caching, queues, rate limiting |
database |
vector-databases |
Semantic search & RAG retrieval |
database |
mongodb |
Flexible NoSQL documents |
desktop |
electron |
Electron cross-platform apps |
devops |
aws-lambda |
Serverless on AWS Lambda |
devops |
cloud-native-ai |
Cloud-native AI platforms |
devops |
docker |
Containers & deployment |
devops |
github-actions |
CI/CD pipelines on GitHub |
devops |
gitlab-ci |
GitLab CI/CD pipelines |
devops |
kubernetes |
Container orchestration |
devops |
observability-llm |
LLM observability |
devops |
platform-engineering |
Internal developer platforms |
devops |
serverless-ai |
Serverless AI workloads |
devops |
sre-slos |
SLOs & reliability |
devops |
terraform |
Infrastructure as code |
devops |
kafka |
Event streaming platform |
devops |
prometheus-grafana |
Metrics & dashboards |
embedded |
rust-embedded |
Embedded Rust |
engineering |
ai-testing |
AI/LLM testing |
engineering |
code-review |
Effective code reviews |
engineering |
git-workflow |
Git branching & history hygiene |
engineering |
claude-code-commands |
Claude Code commands & hooks |
frontend |
bun-runtime |
Bun runtime & tooling |
frontend |
nextjs |
Next.js full-stack React |
frontend |
react-19 |
Modern React UIs |
frontend |
tailwind-v4 |
Tailwind CSS v4 |
frontend |
typescript |
Type-safe JavaScript |
frontend |
vue |
Vue 3 reactive UIs |
finance |
algorithmic-trading |
Backtesting & strategy design |
finance |
risk-modeling |
VaR, CVaR & stress testing |
gamedev |
game-physics |
2D/3D physics & collisions |
gamedev |
unity-ecs |
Unity ECS & DOTS |
healthcare |
hipaa-compliance |
HIPAA security & privacy |
healthcare |
hl7-fhir |
FHIR integrations |
mobile |
expo-rn |
Expo & React Native |
mobile |
flutter |
Cross-platform Flutter apps |
qa |
browser-automation |
Playwright E2E & scraping |
qa |
pytest |
Reliable Python testing |
security |
oauth2-jwt |
OAuth 2.0 & JWT |
security |
owasp-web-security |
OWASP Top 10 hardening |
SDK
Python
from claude_skills.catalog import CatalogBuilder
from claude_skills.validator import ValidationPipeline
from claude_skills.quality import QualityAnalyzer
catalog = CatalogBuilder().build_catalog()
print(f"{catalog.metadata.total_skills} skills, {catalog.metadata.total_ru} RU")
pipeline = ValidationPipeline(Path(".claude/skills"))
report = pipeline.report(pipeline.run_all())
print(f"Errors: {report['errors']}, Warnings: {report['warnings']}")
CLI
Commands: stats, search, validate, quality, catalog.
agent-skills search <query> # Search by name, description, tags
agent-skills validate --json out.json
agent-skills quality --json out.json
agent-skills catalog # Rebuild catalog JSON
agent-skills stats # Library statistics
GitHub Action
Validate, score, and catalog skills in your own repo with the Claude Skills Action:
name: Validate skills
on:
pull_request:
jobs:
validate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ssrjkk/agent-skills@v3.4.0
with:
command: validate
target: .claude/skills
Quality Pipeline
Every skill is scored on 5 dimensions:
| Dimension | Weight | What it measures |
|---|---|---|
| Completeness | 25% | Section coverage (Quick Start, Validation, etc.) |
| Depth | 25% | Content length & substance |
| Code Quality | 20% | Working code examples |
| Freshness | 15% | Recency of last update |
| Bilingual | 15% | Russian translation quality |
Domains (16)
ai · backend · blockchain · data · database · desktop · devops ·
embedded · engineering · finance · frontend · gamedev · healthcare ·
mobile · qa · security
Author
ssrjkk — creator & maintainer
For Contributors
See CONTRIBUTING.md. Quick checklist:
-
SKILL.mdhas frontmatter with name, description, category, tags, models, version -
SKILL.ru.mdis a real translation (not auto-generated) - Code examples compile and run
-
SKILL.mdpassesscripts/check_agent_interop.py(portable to all agents) -
make testpasses -
make lintpasses
Links
Why this library
- Curated, not generated — 65 hand-reviewed skills that pass a 5-dimension quality pipeline (completeness, depth, code quality, freshness, bilingual).
- Universal Agent Skills format — the same
SKILL.mdconvention native to Claude Code and supported by OpenCode, Cursor, Windsurf, and others. No lock-in: install once, use anywhere. - Bilingual (EN + RU) — every skill ships a real Russian translation, not a machine one.
- Works across every LLM/GLM ecosystem — skills are written to work with Claude (Sonnet/Opus), OpenAI (GPT), Google (Gemini), and Zhipu GLM models.
- Quality enforced in CI — validation, quality scoring, anti-pattern
detection, cross-agent interop checks, 100% test coverage. What you see in
mainis what passes the bar. - SDK + CLI + GitHub Action — validate, score, catalog and search any skills library programmatically.
Supported agents & models
The SKILL.md format is universal — every skill works with any agent that
implements the Agent Skills spec, across model providers:
Legacy Version
The original v1.0 library (10,000+ auto-generated skills) is archived under
the v1.0-legacy tag — v3.1 is a complete rewrite focused on quality:
git checkout v1.0-legacy
License
MIT.
Metadata
Release files for agent-skills-library 3.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agent_skills_library-3.4.1.tar.gz | 26.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agent_skills_library-3.4.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 46.0 kB
Release files / agent_skills_library-3.4.1.tar.gz
| Download URL | agent_skills_library-3.4.1.tar.gz |
|---|---|
| Size | 26.7 kB |
| Tags | Source |
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Release files / agent_skills_library-3.4.1-py3-none-any.whl
| Download URL | agent_skills_library-3.4.1-py3-none-any.whl |
|---|---|
| Size | 19.3 kB |
| Tags | Python 3 |
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