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?
100 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 | 100 |
| Russian translations | 100 (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 |
agent-development |
Build reliable LLM agents and agentic workflows: tool use, memory, loops, guardrails, and evaluation |
ai |
context-engineering |
Curate LLM context windows for quality and cost: system prompts, compaction, just-in-time retrieval, progressive disclosure, and token budgets |
ai |
embeddings |
Work with text embeddings: model selection, vectorization, similarity, clustering, and caching for search and retrieval |
ai |
few-shot-learning |
Designs and curates few-shot examples to guide LLM behavior, including example selection, formatting, and ordering |
ai |
function-calling |
Implement robust LLM function/tool calling: schemas, multi-call handling, validation, error recovery, and structured execution |
ai |
llm-evals |
Build evaluation suites for LLM applications: golden datasets, metrics, LLM-as-judge, regression gates, and CI integration |
ai |
llm-finetuning |
Fine-tunes open-source LLMs (Llama, Mistral, Qwen) using LoRA/QLoRA with HuggingFace and Unsloth |
ai |
llm-guardrails |
Add safety guardrails to LLM apps: prompt injection defense, content filtering, PII protection, policy enforcement, and red-teaming |
ai |
mcp-servers |
Build Model Context Protocol servers and clients: tools, resources, prompts, transport, and secure agent integration |
ai |
mlops |
Operate machine learning in production: experiment tracking, pipelines, model registry, serving, monitoring, and CI/CD for ML |
ai |
multi-agent-orchestration |
Design and run multi-agent systems: orchestrator-worker, routing, handoffs, shared state, and coordination patterns |
ai |
prompt-caching |
Optimize LLM cost and latency with prompt caching: cacheable prefixes, cache-control headers, context layout, and cache-aware prompting |
ai |
prompt-engineering |
Design effective prompts for LLMs: role framing, structured output, chain-of-thought, few-shot, and evaluation |
ai |
rag-pipeline |
Build retrieval-augmented generation pipelines: chunking, embeddings, vector search, hybrid retrieval, and citation |
ai |
structured-output |
Force LLMs to emit valid, schema-constrained structured output: JSON modes, function calling, JSON Schema validation, and error recovery |
backend |
deno-runtime |
Deno runtime and standard library |
backend |
django |
Build secure web applications with Django: models, views, ORM, admin, auth, REST APIs, and deployment |
backend |
dotnet |
Build |
backend |
express |
Build Node |
backend |
fastapi |
Build high-performance Python APIs with FastAPI: routing, Pydantic validation, async, dependency injection, OpenAPI, and testing |
backend |
go-rest-api |
Build production REST APIs in Go with the standard library or Gin, including routing, middleware, JSON handling, and testing |
backend |
graphql |
Design and implement GraphQL APIs: schemas, resolvers, queries, mutations, subscriptions, and N+1 avoidance |
backend |
grpc |
Build high-performance services with gRPC: protobuf schemas, unary/streaming RPCs, interceptors, and error handling |
backend |
laravel |
Build PHP web applications with Laravel: routing, Eloquent ORM, Blade, migrations, validation, and deployment |
backend |
nestjs |
Creates Node |
backend |
rest-api-design |
Design consistent REST APIs: resource modeling, status codes, pagination, versioning, error contracts, and documentation |
backend |
rust-tokio |
Async Rust with Tokio runtime |
backend |
spring-boot |
Build production Java/Kotlin backends with Spring Boot: REST controllers, dependency injection, data access, security, and testing |
backend |
websockets |
Build real-time features with WebSockets: connection lifecycle, protocols, backpressure, scaling, and reconnection |
blockchain |
zk-proofs |
Zero-knowledge proof development |
data |
airflow |
Orchestrate data pipelines with Apache Airflow: DAGs, tasks, dependencies, sensors, and retries |
data |
apache-spark |
Process large-scale data with Apache Spark: DataFrames, SQL, joins, partitioning, and optimization |
data |
data-visualization |
Create clear data visualizations with Matplotlib, Plotly, and Altair: chart selection, design, interactivity, and dashboards |
data |
dbt |
Build analytics engineering workflows with dbt: models, tests, sources, macros, and documentation |
data |
elasticsearch |
Design and operate Elasticsearch: mappings, indexing, queries, aggregations, and cluster tuning |
data |
pandas |
Analyze and transform tabular data with pandas: dataframes, cleaning, aggregation, joins, and time series |
data |
sql-querying |
Write correct and efficient SQL: joins, aggregations, window functions, CTEs, and query optimization |
database |
clickhouse |
Design and operate ClickHouse for OLAP analytics: columnar tables, engines, aggregations, partitioning, and performance |
database |
mongodb |
Design and operate MongoDB: document modeling, queries, indexes, aggregation, replication, and sharding |
database |
mysql |
Design and operate MySQL: schema, InnoDB tuning, indexing, transactions, replication, and query optimization |
database |
postgresql |
Design and operate PostgreSQL databases: schema design, indexing, query optimization, transactions, and migrations |
database |
prisma-orm |
Models databases and writes type-safe queries with Prisma ORM |
database |
redis |
Use Redis for caching, sessions, queues, rate limiting, and pub/sub: data structures, persistence, eviction, and clustering |
database |
sqlite |
Use SQLite for embedded relational storage: schema, WAL mode, transactions, indexing, and performance |
database |
vector-databases |
Design and operate vector databases for semantic search and RAG: embeddings, indexes (HNSW), filtering, hybrid search, and scaling |
desktop |
electron |
Builds cross-platform desktop applications with Electron, React, and IPC communication |
devops |
ansible |
Automate infrastructure with Ansible: playbooks, roles, inventory, modules, and idempotency |
devops |
argocd |
Deploy applications on Kubernetes with Argo CD: GitOps, applications, sync policies, health checks, and rollbacks |
devops |
aws-lambda |
Builds and deploys serverless functions with AWS Lambda, API Gateway, and SAM/CDK |
devops |
cloud-native-ai |
Cloud-native AI deployment patterns |
devops |
docker |
Containerize applications with Docker: Dockerfiles, images, networking, volumes, compose, and production hardening |
devops |
github-actions |
Automate CI/CD with GitHub Actions: workflows, jobs, matrices, caching, artifacts, and reusable workflows |
devops |
gitlab-ci |
Configures GitLab CI/CD pipelines with stages, jobs, and GitLab Runner |
devops |
istio |
Operate a service mesh with Istio: sidecars, traffic routing, mTLS, observability, and resiliency |
devops |
jenkins |
Operate Jenkins CI/CD: pipelines as code, agents, shared libraries, credentials, and plugins |
devops |
kafka |
Design and operate Kafka event streaming: topics, producers, consumers, consumer groups, partitioning, and exactly-once |
devops |
kubernetes |
Deploy and operate applications on Kubernetes: workloads, services, config, scaling, and GitOps |
devops |
loki |
Operate log aggregation with Grafana Loki: agents, labels, queries (LogQL), retention, and dashboards |
devops |
nginx |
Configure and operate Nginx: reverse proxy, load balancing, TLS, caching, and security headers |
devops |
observability-llm |
LLM observability with Langfuse/LangSmith |
devops |
platform-engineering |
Platform engineering with Backstage/Port |
devops |
prometheus-grafana |
Set up monitoring with Prometheus and Grafana: metrics, exporters, alerting rules, dashboards, and SLO tracking |
devops |
serverless-ai |
Serverless AI inference (Cloudflare Workers, Lambda) |
devops |
sre-slos |
SRE SLI/SLO/SLA implementation |
devops |
terraform |
Provision infrastructure as code with Terraform: resources, modules, state, workspaces, and remote backends |
embedded |
rust-embedded |
Rust for embedded systems |
engineering |
ai-testing |
AI-powered test generation and validation |
engineering |
claude-code-commands |
Use Claude Code effectively: slash commands, context management, hooks, MCP, permissions, and workflows |
engineering |
clean-architecture |
Structure codebases with clean architecture: layers, dependency rule, use cases, ports and adapters |
engineering |
code-review |
Conduct effective code reviews: correctness, security, performance, style, and actionable feedback |
engineering |
git-workflow |
Use Git effectively: branching, commits, rebase vs merge, history hygiene, conflict resolution, and collaboration workflows |
engineering |
system-design |
Design scalable systems: requirements, architecture, data models, trade-offs, and scaling strategies |
engineering |
test-driven-development |
Practice test-driven development: red-green-refactor, test design, refactoring safely, and coverage discipline |
finance |
algorithmic-trading |
Build algorithmic trading systems: backtesting, strategy design, order execution, risk management, and market data pipelines |
finance |
risk-modeling |
Build financial risk models: VaR, CVaR, Monte Carlo simulation, stress testing, and portfolio risk decomposition |
frontend |
angular |
Build enterprise web apps with Angular: components, signals, services, dependency injection, and testing |
frontend |
astro |
Build content-focused websites with Astro: islands architecture, content collections, static generation, and integrations |
frontend |
bun-runtime |
Bun runtime for JavaScript/TypeScript |
frontend |
modern-css |
Use modern CSS: layout (grid/flex), custom properties, container queries, cascade layers, and responsive design |
frontend |
nextjs |
Build full-stack React applications with Next |
frontend |
react-19 |
Build modern user interfaces with React 19, including Server Components, Actions, hooks, and the new compiler |
frontend |
svelte |
Build reactive UIs with Svelte 5: runes, stores, components, and transitions |
frontend |
tailwind-v4 |
Tailwind CSS v4 features |
frontend |
typescript |
Apply TypeScript for type-safe JavaScript: type design, generics, utility types, strict mode, and integration with modern tooling |
frontend |
vue |
Build reactive user interfaces with Vue 3: Composition API, reactivity, components, state, and tooling |
gamedev |
game-physics |
Implement 2D/3D game physics: rigid bodies, collisions, constraints, raycasting, and performance optimization |
gamedev |
unity-ecs |
Build scalable Unity games with Entity Component System (ECS): systems, queries, jobs, burst compilation, and DOTS patterns |
healthcare |
hipaa-compliance |
Implement HIPAA compliance in healthcare software: PHI protection, access controls, audit logging, encryption, and breach notification |
healthcare |
hl7-fhir |
Build healthcare integrations with HL7 FHIR: resources, operations, SMART on FHIR apps, and clinical data exchange |
mobile |
expo-rn |
Expo SDK for React Native development |
mobile |
flutter |
Build cross-platform mobile apps with Flutter: widgets, state management, navigation, platform channels, and release builds |
mobile |
kotlin-android |
Build Android apps with Kotlin: Compose UI, coroutines, architecture components, and Gradle |
mobile |
swift-ios |
Build iOS apps with Swift and SwiftUI: views, state, navigation, concurrency, and Combine |
qa |
browser-automation |
Automate browsers with Playwright: selectors, waits, assertions, screenshots, network interception, and CI |
qa |
jest |
Write reliable JavaScript tests with Jest: unit tests, mocking, snapshots, coverage, and CI integration |
qa |
pytest |
Write reliable Python tests with pytest: fixtures, parametrize, mocking, async tests, and CI integration |
security |
api-security |
Secure web APIs: authentication, authorization, rate limiting, input validation, and abuse protection |
security |
oauth2-jwt |
Implements OAuth 2 |
security |
owasp-web-security |
Harden web applications against the OWASP Top 10: injection, XSS, auth flaws, CSRF, SSRF, and insecure dependencies |
security |
secrets-management |
Manage secrets safely: vaults, rotation, environment variables, scanning, and least privilege |
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@v3.5.0
with:
command: validate # validate | quality | catalog | stats
target: .claude/skills # path to skills directory
output: skills_catalog.json
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 — 100 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 4.0.0
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-4.0.0.tar.gz | 38.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agent_skills_library-4.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 60.9 kB
Release files / agent_skills_library-4.0.0.tar.gz
| Download URL | agent_skills_library-4.0.0.tar.gz |
|---|---|
| Size | 38.3 kB |
| Tags | Source |
|
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|---|---|
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