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Skill Finder
Discover and install agent skills from the skills.sh open ecosystem into Skill Compose.
When to Use This Skill
Activate when users:
- Ask "how do I do X?" where an existing skill might help
- Request "find a skill for X" or "is there a skill for X?"
- Ask "can you do X?" for specialized tasks (poster design, data analysis, etc.)
- Want to search for tools, templates, or workflows
- Mention needing help with a specific domain that might have a community skill
Available Scripts
1. Search Skills — find_skills.py
Search the skills.sh ecosystem for skills matching a query.
python scripts/find_skills.py <query> [--limit N]
Example:
python scripts/find_skills.py "react performance"
python scripts/find_skills.py "docker" --limit 5
Output: JSON array of matching skills with name, source (owner/repo), installs count, and url (skills.sh link).
2. Install Skill — add_skill.py
Download a skill from GitHub and register it in Skill Compose.
python scripts/add_skill.py <owner/repo@skill-name>
Example:
python scripts/add_skill.py "vercel-labs/agent-skills@vercel-react-best-practices"
What it does:
- Parses the
owner/repo@skill-nameidentifier - Tries multiple GitHub paths to locate the skill (
skills/<name>/,<name>/, root) - Downloads all skill files (SKILL.md, scripts/, references/, assets/)
- Saves to the local
skills/directory - Registers the skill in Skill Compose via the import-local API
- The skill is immediately available for use in Agent Presets
CRITICAL: Never Combine Questions with Tool Calls
When you ask the user a question or present results for them to review, your response MUST end with text only. Do NOT include any tool call (execute_code, bash, etc.) in the same response. The user needs a chance to read and reply. If you combine a question with a tool call, the tool executes immediately without waiting — this breaks the conversation flow.
WRONG (never do this):
"Should I install X?" + [execute_code: install X]
CORRECT (always do this):
Turn 1: "Should I install X?" (text only, no tool calls) Turn 2: User says "yes" Turn 3: [execute_code: install X]
How to Help Users Find and Install Skills
Each step below MUST be a separate conversation turn. Never combine steps.
Step 1: Understand the Need
Identify what domain and specific task the user needs help with.
Step 2: Search
Run find_skills.py with relevant keywords. Try multiple queries if the first doesn't yield good results. Even if the user names an exact skill, always search first to find the correct source/owner and verify it exists.
Step 3: Present Results and Ask
Show the user the found skills with:
- Skill name
- Source repository
- Install count (popularity indicator)
- skills.sh link for more details
Ask which skill(s) they want to install. End your response here — no tool calls.
Step 4: Confirm
When the user picks a skill, repeat back what you will install and ask for confirmation. This must be a text-only response with no tool calls. Wait for the user to reply.
Step 5: Install
Only after the user confirms in a separate message, run add_skill.py. Report the result.
Common Skill Categories
| Category | Example Queries |
|---|---|
| Web Development | react, nextjs, vue, css, tailwind, html |
| Testing | testing, jest, playwright, cypress |
| DevOps | docker, kubernetes, ci-cd, terraform |
| Documentation | docs, readme, markdown, api-docs |
| Code Quality | lint, refactor, code-review, typescript |
| Design | ui, design, figma, accessibility |
| Data & ML | pandas, data-analysis, machine-learning |
| Productivity | git, automation, workflow |
Tips for Effective Searches
- Use specific domain keywords: "react performance" instead of just "fast"
- Try alternative terms if first search yields few results: "testing" → "jest" → "playwright"
- Popular skill sources include:
vercel-labs/agent-skills,google-labs-code/stitch-skills - Check install counts — higher counts generally indicate more mature skills
When No Skills Are Found
- Acknowledge that no matching skill exists yet
- Offer to help the user directly with their task
- Suggest the user could create a custom skill for their use case using
skill-creator
- 流狐分类
- AI 智能
- 作者声明 Agent
- 未找到明确声明;不据此推断已兼容或已测试
- 静态检查
- 88 / 100 · 启发式扫描,不代表运行安全
- 作者 / 版本 / 许可
- @dp-archive · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 需手动接入
- 是否需要外部 API Key
- 需要 · GitHub
- 检测到的系统要求
- Docker
- 底层运行要求
- Python · Docker
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 检测到的网络行为
- 允许外网请求
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
# Step 3: Present Results and Ask
- Skill name
- Source repository
- Install count (popularity indicator)
- skills.sh link for more details Identify what domain and specific task the user needs help with.
Run findskills.py with relevant keywords. Try multiple queries if the first doesn't yield good results. Even if the user names an exact skill, always search first to find the correct source/owner and verify it exists.
Show the user the found skills with: Skill name Source repository
When the user picks a skill, repeat back what you will install and ask for confirmation. This must be a text-only response with no tool calls. Wait for the user to reply.
# Skill Finder
Discover and install agent skills from the [skills.sh](https://skills.sh) open ecosystem into Skill Compose.
## When to Use This Skill
Activate when users:
- Ask "how do I do X?" where an existing skill might help
- Request "find a skill for X" or "is there a skill for X?"
- Ask "can you do X?" for specialized tasks (poster design, data analysis, etc.)
- Want to search for tools, templates, or workflows
- Mention needing help with a specific domain that might have a community skill
## Available Scripts
### 1. Search Skills — `find_skills.py`
Search the skills.sh ecosystem for skills matching a query.
```bash
python scripts/find_skills.py <query> [--limit N]
```
**Example:**
```bash
python scripts/find_skills.py "react performance"
python scripts/find_skills.py "docker" --limit 5
```
**Output:** JSON array of matching skills with `name`, `source` (owner/repo), `installs` count, and `url` (skills.sh link).
### 2. Install Skill — `add_skill.py`
Download a skill from GitHub and register it in Skill Compose.
```bash
python scripts/add_skill.py <owner/repo@skill-name>
```
**Example:**
```bash
python scripts/add_skill.py "vercel-labs/agent-skills@vercel-react-best-practices"
```
**What it does:**
1. Parses the `owner/repo@skill-name` identifier
2. Tries multiple GitHub paths to locate the skill (`skills/<name>/`, `<name>/`, root)
3. Downloads all skill files (SKILL.md, scripts/, references/, assets/)
4. Saves to the local `skills/` directory
5. Registers the skill in Skill Compose via the import-local API
6. The skill is immediately available for use in Agent Presets
## CRITICAL: Never Combine Questions with Tool Calls
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> When to Use This Skill → Available Scripts → 1. Search Skills — findskills.py → 2. Install Skill — addskill.py → CRITICAL: Never Combine Questions with Tool Calls → How to Help Users Find and Install Skills
要点 -> Example · Output · What it does · WRONG · CORRECT · End your response here — no tool calls. · This must be a text-only response with no tool calls. · separate message
文件/命令 -> findskills.py · name · source · installs · url · addskill.py · owner/repo@skill-name · skills/<name>/
内容 SHA-256 -> 68326579fa77
方法与流程
适用与边界
原文中的明确线索
findskills.py、name、source、installs、url、addskill.py、owner/repo@skill-name、skills/<name>/