by wheelry
Deep Skill Finder – Find the right Skill for every Agent task
# Add to your Claude Code skills
git clone https://github.com/wheelry/deep-skill-finderGuides for using ai agents skills like deep-skill-finder.
deep-skill-finder is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by wheelry. Deep Skill Finder – Find the right Skill for every Agent task. It has 40 GitHub stars.
deep-skill-finder's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/wheelry/deep-skill-finder" and add it to your Claude Code skills directory (see the Installation section above). deep-skill-finder ships a SKILL.md manifest, so compatible agents can discover and load it automatically.
deep-skill-finder is primarily written in Python. It is open-source under wheelry on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh deep-skill-finder against similar tools.
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Unlocks once the catalog security scan passes (runs nightly).
The deep catalog scan for this skill is still queued. Run an instant dependency check now instead.
先判断用户输入是否包含明确的 skill 需求:如果描述太模糊(如只说"找个skill""推荐个技能"),先检查对话上下文中是否有可推断的需求,如有则基于上下文发起检索;如无则追问用户想找什么方向的 skill,拿到具体描述后再检索。
拿到具体需求后,先按下方「Agent 类型识别」识别当前 Agent 类型,再将用户的任务描述作为请求,调用如下接口,脚本会使用觅游社区的 Skill 检索服务进行意图理解、搜索召回并按相关性排序,最终输出5个以内的推荐skill。
{skill_dir} 为当前 deep-skill-finder skill 自身的目录(区别于下方安装检查中的 {skills_dir})。
{python} {skill_dir}/scripts/deep_skill_search.py "<用户任务描述>" --agent-type <你的Agent类型,详见Agent 类型识别章节>
{python}需按本机实际选择:macOS/Linux 通常为python3,Windows 通常为python或py。下同。
根据接口的返回结果,按照如下输出规则处理,按照输出模板输出给用户: 输出规则:
输出模板(严格参照以下格式输出,将占位符替换为实际值):
为你找到以下相关 skill:
# Skill 推荐理由 1 {name} {reason} 2 {name} {reason} ... ... ... 最优推荐是 #1 {name}({reason})。你想安装哪一个?告诉我编号或名字就行。
异常处理: 脚本执行出错时,禁止将原始错误信息(如 "The read operation timed out")直接展示给用户,需按以下规则处理:
| 异常场景 | 处理方式 | 输出示例 |
|---|---|---|
| 搜索超时 | 自动重试最多 3 次(无需告知用户重试过程),仍失败则告知用户 | "搜索服务暂时不可用,请稍后再试。" |
| 返回 0 条结果 | 告知用户换描述重试 | "没有找到完全匹配的 skill,建议换个关键词或更简短的描述再试一次。" |
| 网络错误 / 连接失败 | 告知用户网络问题 | "网络连接异常,请检查网络后重试。" |
| 脚本执行报错(其他) | 翻译为用户友好的中文提示 | "搜索服务遇到了一点问题,建议稍后重试。如持续出现,可反馈给 skill 作者。" |
当用户通过以下方式确认选择时,进入安装流程:
确认用户选择后,进行本地检查:检查 {skills_dir}/{name}/SKILL.md 是否存在({skills_dir} 为当前 Agent 的 skills 目录,{name} 为用户选择的 skill 名称)。若存在则视为已安装,告知用户"该 skill 已安装,无需重复安装,是否直接运行?";若不存在,则执行安装流程:
{python} {skill_dir}/scripts/deep_skill_install.py <name> --dir <当前 Agent 的 skills 目录> --agent-type <你的Agent类型,详见Agent 类型识别章节>
安装脚本执行后,根据退出状态输出结果:
| 命令 | 用途 |
|---|---|
deep_skill_search.py |
根据用户任务检索skill |
deep_skill_install.py |
下载安装 skill |
为了得到更精准的搜索结果,调用搜索/下载脚本时需要上报当前 Agent 类型信息(agent-type)。请按以下方式识别:
从环境变量识别(首选):检查是否存在 <APP>_USER_DATA_DIR 格式的环境变量,提取其路径末尾的目录名作为 Agent 类型
QCLAW_USER_DATA_DIR → QClawHERMES_DATA_DIR → Hermes从 system prompt 识别:若你的运行环境提供 system prompt(如 Catdesk、Hermes 等),从中识别 Agent 框架名称
从 IDENTITY.md 识别:若以上均无法识别,检查本地 IDENTITY.md 是否存在并包含 ## 标识 小节,从其中提取 App 名称
自行判断:若以上均无法识别,根据你所在的运行时框架自行判断,可省略该参数,脚本会正常执行但不带 agent_type 上报
调用安装脚本时需要指定 --dir 参数为目标 Agent 的 skills 目录。确定方式:
<APP>_USER_DATA_DIR 环境变量,在其路径下查找 skills/ 子目录
若环境变量路径下无 skills/ 子目录,则退回到工作区查找。skills/ 子目录(含 SKILL.md 即为有效)--list 参数验证目录是否正确,返回已安装列表即说明路径有效以下是一个完整的端到端交互示例,展示从搜索到安装的全流程:
用户:找个写小红书爆款帖子的skill
Agent 执行:
{python} {skill_dir}/scripts/deep_skill_search.py "写小红书爆款帖子" --agent-type openclaw
Agent 输出:
为你找到以下相关 skill:
# Skill 推荐理由 1 qf-xiaohongshu-writer 爆款笔记生成器,内置标题公式和内容模板,擅长情绪共鸣和种草风格 2 rednote-creator 小红书全流程创作技能,覆盖美妆护肤等六大赛道 3 rednote-writer-pro 专注爆款文案生成,覆盖美妆赛道 最优推荐是 #1 qf-xiaohongshu-writer(爆款笔记生成器,内置标题公式和内容模板)。你想安装哪一个?告诉我编号或名字就行。
用户:1
Agent 检查:确认本地未安装 qf-xiaohongshu-writer,执行安装。
Agent 执行:
{python} {skill_dir}/scripts/deep_skill_install.py qf-xiaohongshu-writer --dir <当前 Agent 的 skills 目录> --agent-type <你的Agent类型,详见Agent 类型识别章节>
Agent 输出: ✅ qf-xiaohongshu-writer 已安装成功。要用这个 skill 来完成你的任务吗?

English | 中文
Deep-skill-finder search powered by real execution and validation, not just follow creator claims
deep-skill-finder crawls Skills across the web, builds an evaluable candidate pool, and uses multi-channel recall to precisely match the best-fit Skill for your current task. It distills millions of real community test records and Skill benchmark reports so you can identify verified, safe, and effective options before installing.
Please install the deep-skill-finder skill: download the skill package from https://www.meyo.life/api/v1/skill-finder, extract it to the local skills directory, and enable it.
Talk to your Agent in natural language — no special syntax needed. When a task requires an external Skill, the Agent automatically triggers the search and installation flow. Examples:
"Find me a skill that builds interactive dashboards from a CSV"
"Is there a skill for pulling stock market data?"
"Recommend a skill for translating technical docs into plain English"
"I need to set up a CI/CD pipeline for my repo, find me a skill that writes GitHub Actions configs that actually run"
"I'm building an AI product and need a business plan, find me a skill that helps structure the logic and polish the deck"
"I want to batch-transcribe audio interviews into clean text, find me a skill that does this end to end"
The Agent returns a ranked list of up to 5 recommendations with reasons. Confirm a number and the installation completes automatically.
Standard marketplace search has two fundamental problems:
Discovery — creators write broad, abstract descriptions to rank in more searches. When your specific task comes in, keyword matching buries the best match under noise.
Trust — download counts and star ratings can't tell you whether a Skill ever actually ran correctly. Broken dependencies, edge cases, and overpromising stay invisible until you're already in the pit.
deep-skill-finder addresses both: it recalls by actual task behavior, and ranks by real community run results — not by what a creator claims their Skill does.
Web-wide Skill indexing — crawls Skill content across the web and builds an evaluable candidate pool, independent of any single platform's popularity ranking.
Community-scale test records — distills real tasks, run results, and benchmark reports from the community into a searchable Skill track-record database.
Multi-channel recall — pulls simultaneously from Skill capability descriptions, community test posts, and real outputs, preventing any single signal from missing the best candidate.
Autonomous workflow loop — once installed, it runs persistently in your Agent and autonomously handles: identify need → multi-channel recall → confirm install → execute task → feed results back. Each match gets more accurate over time.
Intent-driven precision — matches by understanding real task intent rather than description keywords, so specific needs surface the truly relevant Skill instead of being drowned out by generic descriptions.
Track-record-based ranking — ranks candidates by real pass rate and output quality, so you don't have to guess between multiple seemingly viable Skills.
Risk exposure before install — surfaces known failure points and boundary conditions accumulated from community testing, so you know which Skills have issues before committing, not after.
You describe a task in natural language
│
▼
Intent understanding
(rewrite into semantic query)
│
▼
Multi-channel recall
┌─────────┬──────────────┐
│ Skill │ Community │
│ profile │ test posts │
└────┬────┴──────┬───────┘
└─────┬─────┘
▼
Rank by verified track record
→ return TOP 5 with reasons
│
▼
Confirm a number → auto-install
├── SKILL.md # Skill definition (read by the Agent)
└── scripts/
├── deep_skill_search.py # Semantic search via Meyo retrieval service
└── deep_skill_install.py # Download and install a Skill locally
You normally don't call these directly — the Agent handles invocation. But you can run them standalone:
Search
python3 scripts/deep_skill_search.py "your task description" [--agent-type openclaw]
Install / Uninstall / List
# Install
python3 scripts/deep_skill_install.py <skill-name> --dir ~/.catpaw/skills
# Uninstall
python3 scripts/deep_skill_install.py <skill-name> --dir ~/.catpaw/skills --uninstall
# List installed
python3 scripts/deep_skill_install.py --dir ~/.catpaw/skills --list
Issues and pull requests are welcome.
If you find that a specific Skill is ranked too high or too low, the underlying signal lives in the Meyo community — leaving a real test report there is the most direct way to improve future recommendations.
Released under the MIT License. Free to use, modify, and distribute — attribution appreciated.