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Claude Skills

The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.

Every Agent Skill we could find on GitHub, deduplicated by content. 79 354 files from 1 739 authors, of which 61 713 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.

61 713
unique skills
out of 79 354 files found on GitHub
17 641
are copies
same content, someone else's repository
1 738
tokens, median
what a typical skill costs you in context
7 879
name collisions
two skills with one name cannot sit side by side

57 841–57 900 of 61 713

page 965 of 1 029
Snapshot
by chaterm

快照管理

949 tokens
Azure CLI
by chaterm

Azure CLI 操作

2k tokens
Postgresql
by chaterm

PostgreSQL 数据库管理

1k tokens
Elasticsearch
by chaterm

Elasticsearch 集群管理

2k tokens
Redis
by chaterm

Redis 数据库管理

1k tokens
SQL Optimization
by chaterm

SQL 优化与调优

2k tokens zh
Gcloud
by chaterm

Google Cloud CLI 操作

2k tokens
Mongodb
by chaterm

MongoDB 数据库管理

1k tokens
Mysql
by chaterm

MySQL 数据库管理与运维

784 tokens zh
Ansible
by chaterm

Ansible 自动化运维

2k tokens
Git Advanced
by chaterm

Git 高级操作

2k tokens zh
CI CD
by chaterm

CI/CD 流水线配置

2k tokens
Compose
by chaterm

Docker Compose 编排

2k tokens
Terraform
by chaterm

Terraform 基础设施即代码

2k tokens
Container Ops
by chaterm

Docker 容器操作与管理

827 tokens zh
Monitoring
by chaterm

监控与告警

2k tokens
Dockerfile
by chaterm

Dockerfile 编写最佳实践

2k tokens
Image Management
by chaterm

Docker 镜像管理

1k tokens
Networking
by chaterm

Docker 容器网络

1k tokens zh
Configmap Secret
by chaterm

Kubernetes ConfigMap 与 Secret

2k tokens
Deployment
by chaterm

Kubernetes Deployment 管理

2k tokens
Kubectl Basics
by chaterm

kubectl 基础操作与常用命令

785 tokens
Helm
by chaterm

Helm 包管理

2k tokens
Pod Management
by chaterm

Kubernetes Pod 管理与调试

1k tokens
Service Ingress
by chaterm

Kubernetes Service 与 Ingress

2k tokens
Troubleshooting
by chaterm

Kubernetes 故障排查

2k tokens
File Operations
by chaterm

Linux file and directory operations

1k tokens
Network Tools
by chaterm

Linux network tools and diagnostics

1k tokens
Process Management
by chaterm

Linux process management and control

1k tokens
Shell Scripting
by chaterm

Bash Shell 脚本编写

2k tokens zh
System Admin
by chaterm

Linux system administration and monitoring

511 tokens
User Permissions
by chaterm

Linux user and permission management

1k tokens
DNS
by chaterm

DNS 配置与排查

1k tokens
Load Balancer
by chaterm

负载均衡配置

2k tokens
Traffic Analysis
by chaterm

流量分析与抓包

1k tokens
Proxy
by chaterm

代理服务器配置

2k tokens
Tcp IP
by chaterm

TCP/IP 网络诊断与排查

638 tokens zh
Vpn
by chaterm

VPN 配置与管理

2k tokens
Maintenance
by chaterm

OpenClaw 运维与故障修复

3k tokens
Configuration
by chaterm

OpenClaw 配置管理

3k tokens
Installation
by chaterm

OpenClaw 安装与部署

2k tokens
Troubleshooting
by chaterm

OpenClaw 问题排查与诊断

3k tokens
Benchmarking
by chaterm

性能基准测试

1k tokens
Troubleshooting
by chaterm

性能问题排查

1k tokens zh
Profiling
by chaterm

性能分析

935 tokens zh
Firewall
by chaterm

防火墙配置

1k tokens
Audit
by chaterm

安全审计

1k tokens
Tuning
by chaterm

系统调优

1k tokens
Hardening
by chaterm

系统加固

1k tokens
Ssl Tls
by chaterm

SSL/TLS 证书

1k tokens
Apache
by chaterm

Apache HTTP Server 配置

1k tokens
Cron
by chaterm

定时任务管理

1k tokens zh
Log Analysis
by chaterm

日志分析与处理

1k tokens zh
SSH
by chaterm

SSH 管理与安全

1k tokens zh
Systemd
by chaterm

Systemd 服务管理

1k tokens
Nginx
by chaterm

Nginx configuration and optimization

1k tokens
Secscan
by atgreen

In-session, token-efficient LLM security scan of a repo (SAST triage). A lightweight, native Claude Code pipeline — survey → threat-model → deep-dive → adversarial-verify → report — using Read/Grep/Glob (and optional subagents), no external tooling. Use when asked to "security scan", "find vulnerabilities", "SAST", "audit this code for security", or "secscan".

23k tokens
Research Craft
by nik1t7n

> problems, designing ML/AI experiments, reading papers, building experiment loops, analyzing outputs, writing research notes, or turning vague curiosity into a disciplined research plan. Emphasizes avoiding absorbed problems, upgrading information inputs beyond shared reading lists, and reasoning backward from outcomes the researcher genuinely wants to exist.

3k tokens
Kamae
by iwasa-kosui

| Kamae (構え) — robust server-side TypeScript design. Functional domain modeling with discriminated unions, pure state transitions, Result types, schema-validated boundaries, and PII protection. error handling, boundary validation, or PII handling on the server side; designing types for business logic; implementing entity/value-object semantics in TS. pure infrastructure-as-code; code unrelated to domain logic.

20k tokens scripts
Kamae Review
by iwasa-kosui

| Adversarial code review of server-side TypeScript for adherence to the kamae principles (discriminated unions, branded types, Result error handling, boundary validation, PII protection). involving domain models, repositories, use cases, business logic, or boundary code. unrelated to domain logic.

4k tokens

Claude Skills — questions

Answers built from the skills we actually parsed.

What is a Claude Skill?
A folder with a SKILL.md file: instructions that teach an agent to do one thing well, optionally with scripts and reference files alongside. The format is open and called Agent Skills — Claude Code, Codex and other agents read the same files. It is not a program you run; it is knowledge the agent loads when the task calls for it.
How is a skill different from an MCP server?
A server gives the agent new abilities — it connects to something and exposes tools. A skill gives the agent knowledge: how to use what it already has. They combine, and often literally: 11 329 of the skills here declare which MCP servers they need to work.
Why are there fewer skills here than in other catalogues?
Because we deduplicate by content. Of 79 354 files found on GitHub, 61 713 are unique — the rest is the same skill copied into someone else's repository, word for word. Catalogues that count files rather than skills show every copy as a separate entry.
What does the token count mean?
A skill is loaded into the model's context when it is used, so its size is a running cost on every request that touches it. We measure the whole folder, not just SKILL.md: one official skill is 377 tokens, another drags 83 files of fonts behind it.
How do I install a skill?
Copy the skill folder into ~/.claude/skills for personal use, or into .claude/skills inside a project. The agent picks it up by the name in the SKILL.md header — which is worth checking: 7 879 skills here share a name with another skill, and two of them cannot sit side by side.