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<!-- Awesome Skills -->
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# Awesome Skills
**A curated library of role-based AI skills, organised by professional domain.**
[](./CATALOG.md)
[](./LICENSE)
[](https://github.com/theneoai/awesome-skills/actions/workflows/quality.yml)
[](https://github.com/theneoai/awesome-skills/actions/workflows/comprehensive-evaluation.yml)
[](https://github.com/theneoai/awesome-skills/actions/workflows/pages-deploy.yml)
**[🌐 Website](https://theneoai.github.io/awesome-skills/)** · **[📚 Catalog](./CATALOG.md)** · **[📖 Install Guide](./INSTALL-GUIDE.md)** · **[🤝 Contributing](./CONTRIBUTING.md)**
**Language:** [English](#english) | [中文](#中文)
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---
<a name="english"></a>
## English
### What this is
A library of **956 skill files** (`SKILL.md` + optional `references/`) covering 3 kinds (persona / tool / workflow) across 60+ domains. Each skill is a prompt pack — an instruction set plus reference material — designed to load into Claude Code, OpenCode, Cursor, or similar agent runtimes to give an LLM a consistent professional persona, tool expertise, or engineering workflow methodology.
### What this is NOT
- **Not an alternative to executable skill packs.** The official Anthropic/OpenAI `SKILL.md` convention can ship with `scripts/` and `assets/` that the agent runs. The vast majority of skills here are **persona + methodology**, not runnable tools. Treat them as opinionated system prompts, not as plugins.
- **Not a certification body.** Historical quality scores in this repo were produced by a self-authored scoring script grading against a self-authored rubric. The scoring is useful internally; it is not an independent benchmark.
- **Not feature-complete for every domain.** Coverage is broad but uneven — some categories have deep role hierarchies, others have a single stub.
### Layout
```
skills/ 956 skill files organised by kind
persona/ 827 role-based professional persona skills
<domain>/<role>/
SKILL.md Frontmatter + system prompt (target ≤ 300 lines)
references/ On-demand deep content (workflow / scenarios / …)
EVALUATION_REPORT.md Optional self-scored quality report
tool/ 116 technology-specific expert skills (kind: tool)
<technology>/
<skill-name>/SKILL.md
workflow/ 8 process-driven action skills (kind: workflow)
engineering/ TDD, debug-diagnose, zoom-out, architecture-review,
issue-triage, to-prd
meta/ write-skill, caveman
external/ Registry of curated third-party skill repos
(anthropics/skills, mattpocock/skills, VoltAgent, …).
Pulled on demand via scripts/sync_external.py — not vendored.
benchmarks/ Evaluation dataset + scoring script for comparison
packages/ Curated skill bundles by domain
roadmap/ Career-path documents (independent of skills/)
taxonomy.yml Single source of truth: 21 categories, 80 aliases
tools/ Python package for skill analysis (scoring, tokens, anti-patterns)
scripts/ Maintenance scripts (catalog regen, external sync, taxonomy check, …)
.github/ CI workflows + scripts, CI/CD docs
```
### Quick start
The simplest way to install a skill is to have your agent read its `SKILL.md` URL:
```
Read https://github.com/theneoai/awesome-skills/blob/main/skills/persona/executive/ceo/SKILL.md and install as a skill
```
Platform-specific instructions (OpenCode native command, Claude Code, Cursor, Cline, Codex, Kimi) are in **[INSTALL-GUIDE.md](./INSTALL-GUIDE.md)**.
### Skill packages
Pre-bundled collections in `packages/`:
| Package | Focus |
|---------|-------|
| [tech](./packages/tech.md) | Software, AI/ML, data |
| [executive](./packages/executive.md) | CEO, CTO, CFO, COO, CMO |
| [finance](./packages/finance.md) | Banking, consulting, investment |
| [healthcare](./packages/healthcare.md) | Clinical and medical management |
| [software](./packages/software.md) | Backend, frontend, devops, QA |
### Featured enterprise skills
Role skills modelled after the methodology of specific companies (15 shown out of 100+ under `skills/enterprise/`):
| Skill | Company | Methodology |
|-------|---------|------------|
| [amazon-engineer](./skills/persona/enterprise/amazon/amazon-engineer/SKILL.md) | Amazon | 14 LPs, Working Backwards, 6-page memos |
| [tesla-engineer](./skills/persona/enterprise/tesla/tesla-engineer/SKILL.md) | Tesla | First principles, five-step algorithm |
| [spacex-engineer](./skills/persona/enterprise/spacex/spacex-engineer/SKILL.md) | SpaceX | Rapid iteration, cost innovation |
| [nvidia-ml-engineer](./skills/persona/enterprise/nvidia/nvidia-ml-engineer/SKILL.md) | NVIDIA | CUDA optimisation, GPU platforms |
| [mckinsey-consultant](./skills/persona/enterprise/mckinsey/mckinsey-consultant/SKILL.md) | McKinsey | MECE, issue trees, pyramid principle |
| [toyota-engineer](./skills/persona/enterprise/toyota/toyota-engineer/SKILL.md) | Toyota | TPS, JIT, Kaizen, Jidoka |
| [anthropic-researcher](./skills/persona/enterprise/anthropic/anthropic-researcher/SKILL.md) | Anthropic | Constitutional AI, interpretability |
Full list in [CATALOG.md](./CATALOG.md).
### External ecosystem hub
`external/` is a **registry** of top third-party skill / subagent / plugin repositories —
not a mirror. Pull any subset on demand:
```bash
python3 scripts/sync_external.py --list # see what's registered
python3 scripts/sync_external.py --all # shallow-clone everything
python3 scripts/sync_external.py --slug anthropics-skills
```
Registered sources (see [`external/README.md`](./external/README.md) for the full table):
| Category | Repos |
|----------|-------|
| Official (Anthropic) | [`anthropics/skills`](https://github.com/anthropics/skills), [`claude-plugins-official`](https://github.com/anthropics/claude-plugins-official), [`knowledge-work-plugins`](https://github.com/anthropics/knowledge-work-plugins) |
| Curated lists | [`VoltAgent/awesome-agent-skills`](https://github.com/VoltAgent/awesome-agent-skills), [`hesreallyhim/awesome-claude-code`](https://github.com/hesreallyhim/awesome-claude-code), [`travisvn/awesome-claude-skills`](https://github.com/travisvn/awesome-claude-skills), [`ComposioHQ/awesome-claude-skills`](https://github.com/ComposioHQ/awesome-claude-skills) |
| Subagents & orchestration | [`VoltAgent/awesome-claude-code-subagents`](https://github.com/VoltAgent/awesome-claude-code-subagents), [`wshobson/agents`](https://github.com/wshobson/agents), [`0xfurai/claude-code-subagents`](https://github.com/0xfurai/claude-code-subagents) |
To propose a new source, edit [`external/sources.yml`](./external/sources.yml) and open a PR.
External clones are gitignored and never linted by our CI — we are a pointer, not an enforcer.
### Tooling
The repo ships a Python package for static analysis of skills:
```bash
pip install -e ./tools/
python -m tools.skill_analyzer.cli score # 8-dimension rubric scores
python -m tools.skill_analyzer.cli tokenizer # Token budget + API cost
python -m tools.skill_analyzer.cli antipattern # Common mistakes scanner
```
CI (`.github/workflows/quality.yml`) runs these on any PR that touches `skills/`, `tools/`, or `.github/scripts/`, and **blocks merges** whose changed `SKILL.md` files fall below score/token/description thresholds.
### Known limitations
- **Text-only skills.** Virtually no skill ships executable `scripts/` or `assets/` — they are persona prompts.
- **Description overlap.** The role taxonomy spans 60+ domains and 956 skills and many descriptions overlap, which hurts automatic skill-discovery in agent runtimes. A description-similarity linter runs in CI (informational).
- **Self-scored quality.** `EVALUATION_REPORT.md` files reflect a self-graded rubric, not external review.
- **Three category systems.** `packages/` (14), `roadmap/` (22), and `skills/` (60) use different taxonomies — being consolidated.
### Documentation
| Doc | Purpose |
|-----|---------|
| [CATALOG.md](./CATALOG.md) | Full catalog of all skills |
| [INSTALL-GUIDE.md](./INSTALL-GUIDE.md) | Platform-specific install instructions |
| [CONTRIBUTING.md](./CONTRIBUTING.md) | How to add or improve skills |
| [.github/CI.md](./.github/CI.md) | CI/CD pipeline notes |
### License
MIT — see [LICENSE](./LICENSE).
---
<a name="中文"></a>
## 中文
### 项目定位
按专业领域组织的 **AI Skill 库**，共 **956 个技能**，按 3 种类型（persona / tool / workflow）覆盖 60+ 领域。每个技能是一份 `SKILL.md`（+ 可选 `references/`），本质是**角色化的提示词包**——一套系统指令加参考资料，用于在 Claude Code / OpenCode / Cursor 等 agent 运行时里给 LLM 加载稳定的专业身份、工具专长或工程工作流方法论。
### 不是什么
- **不是可执行 Skill 套件**。Anthropic/OpenAI 官方 `SKILL.md` 可以随包携带 `scripts/` 和 `assets/` 交给 agent 调用；本仓库绝大多数 skill 仅提供**角色 + 方法论**的文本，应视作有观点的系统提示词，而非可运行插件。
- **不是第三方认证**。仓库内历史质量分由本仓库自己编写的脚本按自家标准打出，对内有参考价值，但不是独立基准。
- **不是每个领域都覆盖完整**。分类很广但深浅不一：有些领域有完整角色树，有些只有一个占位文件。
### 目录结构
```
skills/ 956 个技能文件，按 kind 分层组织
persona/ 827 个角色 persona 技能
<domain>/<role>/
SKILL.md Frontmatter + 系统提示词（目标 ≤ 300 行）
references/ 按需加载的深度内容（workflow / scenarios / …）
EVALUATION_REPORT.md 可选：自评质量报告
tool/ 116 个技术工具专家技能（kind: tool）
<technology>/
<skill-name>/SKILL.md
workflow/ 8 个流程驱动工作流技能（kind: workflow）
engineering/ TDD、debug-diagnose、zoom-out、architecture-review、
issue-triage、to-prd
meta/ write-skill、caveman
external/ 精选第三方 skill 仓库的注册表
（anthropics/skills、mattpocock/skills、VoltAgent 等）
通过 scripts/sync_external.py 按需拉取，不随仓库 vendored
benchmarks/ 评估数据集 + 评分脚本
packages/ 按领域打包的 skill 合集
roadmap/ 职业路径文档（独立于 skills/）
taxonomy.yml 21 个分类、80 个别名的唯一真源
tools/ Skill 分析工具 Python 包（评分、token、反模式）
scripts/ 维护脚本（catalog 重生成、external 同步、taxonomy 检查等）
.github/ CI 工作流与脚本、CI/CD 文档
```
### 快速开始
最通用的安装方式是让 agent 读 SKILL.md 的 URL：
```
Read https://github.com/theneoai/awesome-skills/blob/main/skills/persona/executive/ceo/SKILL.md 并安装为 skill
```
各平台（OpenCode 原生命令、Claude Code、Cursor、Cline、Codex、Kimi）详细步骤见 **[INSTALL-GUIDE.md](./INSTALL-GUIDE.md)**。
### Skill 合集
按领域打包，见 `packages/`：
| 合集 | 覆盖 |
|------|------|
| [tech](./packages/tech.md) | 软件、AI/ML、数据 |
| [executive](./packages/executive.md) | CEO、CTO、CFO、COO、CMO |
| [finance](./packages/finance.md) | 银行、咨询、投资 |
| [healthcare](./packages/healthcare.md) | 临床与医疗管理 |
| [software](./packages/software.md) | 后端、前端、devops、QA |
### 精选企业技能
仿照特定公司方法论建模的角色（从 `skills/enterprise/` 100+ 条中选 7 条）：
| Skill | 公司 | 方法论 |
|-------|------|--------|
| [amazon-engineer](./skills/persona/enterprise/amazon/amazon-engineer/SKILL.md) | Amazon | 14 条领导力准则、Working Backwards、6 页备忘录 |
| [tesla-engineer](./skills/persona/enterprise/tesla/tesla-engineer/SKILL.md) | Tesla | 第一性原理、五步算法 |
| [spacex-engineer](./skills/persona/enterprise/spacex/spacex-engineer/SKILL.md) | SpaceX | 快速迭代、成本创新 |
| [nvidia-ml-engineer](./skills/persona/enterprise/nvidia/nvidia-ml-engineer/SKILL.md) | NVIDIA | CUDA 优化、GPU 平台 |
| [mckinsey-consultant](./skills/persona/enterprise/mckinsey/mckinsey-consultant/SKILL.md) | McKinsey | MECE、Issue Tree、金字塔原理 |
| [toyota-engineer](./skills/persona/enterprise/toyota/toyota-engineer/SKILL.md) | Toyota | TPS、JIT、改善、自働化 |
| [anthropic-researcher](./skills/persona/enterprise/anthropic/anthropic-researcher/SKILL.md) | Anthropic | Constitutional AI、可解释性 |
完整列表见 [CATALOG.md](./CATALOG.md)。
### 外部生态集散地
`external/` 是业界优秀 skill / subagent / plugin 仓库的**注册表**（非镜像），按需拉取任意子集：
```bash
python3 scripts/sync_external.py --list # 查看注册的仓库
python3 scripts/sync_external.py --all # 全量浅拉取
python3 scripts/sync_external.py --slug anthropics-skills
```
已注册仓库（完整表格见 [`external/README.md`](./external/README.md)）：
| 类别 | 仓库 |
|------|------|
| 官方（Anthropic） | [`anthropics/skills`](https://github.com/anthropics/skills)、[`claude-plugins-official`](https://github.com/anthropics/claude-plugins-official)、[`knowledge-work-plugins`](https://github.com/anthropics/knowledge-work-plugins) |
| 社区精选列表 | [`VoltAgent/awesome-agent-skills`](https://github.com/VoltAgent/awesome-agent-skills)、[`hesreallyhim/awesome-claude-code`](https://github.com/hesreallyhim/awesome-claude-code)、[`travisvn/awesome-claude-skills`](https://github.com/travisvn/awesome-claude-skills)、[`ComposioHQ/awesome-claude-skills`](https://github.com/ComposioHQ/awesome-claude-skills) |
| Subagent 与编排 | [`VoltAgent/awesome-claude-code-subagents`](https://github.com/VoltAgent/awesome-claude-code-subagents)、[`wshobson/agents`](https://github.com/wshobson/agents)、[`0xfurai/claude-code-subagents`](https://github.com/0xfurai/claude-code-subagents) |
提议新增来源：编辑 [`external/sources.yml`](./external/sources.yml) 并提交 PR。
`external/` 下的本地克隆已加入 `.gitignore`，也不被 CI 扫描——我们是**指针**，不是上游的审阅者。
### 工具
仓库附带 Python 分析包：
```bash
pip install -e ./tools/
python -m tools.skill_analyzer.cli score # 8 维度评分
python -m tools.skill_analyzer.cli tokenizer # Token 预算与 API 成本
python -m tools.skill_analyzer.cli antipattern # 反模式扫描
```
CI（`.github/workflows/quality.yml`）会在修改了 `skills/`、`tools/` 或 `.github/scripts/` 的 PR 上运行这些工具，若新改动的 `SKILL.md` 达不到阈值则**阻塞合并**。
### 已知局限
- **绝大多数 skill 是纯文本 persona**，并不随包携带可执行 `scripts/` 或 `assets/`。
- **描述重叠严重**：60+ 分类 × 956 个技能，许多 description 字段相似度高，会降低 agent 运行时的 skill 自动发现准确度。描述相似度检查已在 CI 中运行（仅提示，不阻塞）。
- **质量分是自评**：`EVALUATION_REPORT.md` 反映仓库自家规则的评分，不是独立评审。
- **三套分类互不一致**：`packages/`（14 类）、`roadmap/`（22 类）、`skills/`（60 类）仍在统一中。
### 文档
| 文档 | 用途 |
|------|------|
| [CATALOG.md](./CATALOG.md) | 完整技能目录 |
| [INSTALL-GUIDE.md](./INSTALL-GUIDE.md) | 各平台安装步骤 |
| [CONTRIBUTING.md](./CONTRIBUTING.md) | 如何贡献或改进技能 |
| [.github/CI.md](./.github/CI.md) | CI/CD 说明 |
### 相关项目
- [Awesome MCPs](https://theneoai.github.io/awesome-mcps/) - 115+ MCP 服务器，一键安装
- [GitHub](https://github.com/theneoai/awesome-mcps) - Awesome MCPs 项目源码
### 许可证
MIT，见 [LICENSE](./LICENSE)。
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