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skillfactoryskillfactory 搜索

Agent Skill

skillfactory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,515

周安装

145

GitHub Stars

公开资料未说明

下载量

1,148
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skillfactory(skillfactory 搜索)
来源仓库:https://github.com/zhelunsun/skillfactory
安装命令:
openclaw skills install skillfactory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install skillfactory

简介

skillfactory 是用于创建和管理 OpenClaw 技能的元技能工具。

  • 适合从想法出发构建新技能,支持迭代开发和发布流程。
  • 提供结构化指导,帮助用户系统化地设计技能功能和元数据。
  • 通过 clawhub 安装,建议参考原始文档了解模板和开发规范。
  • 使用前请评估其是否涉及代码生成或文件系统操作权限。

SKILL.md

name
skill-factory
version
2.2.1
description
>

Skill Factory — The Meta-Skill for Making Skills

"The first industrial revolution was marked by using machines to make machines. Skill Factory is the machine that makes skills."

Purpose

Skill Factory provides a repeatable, human-AI collaborative SOP for going from a raw idea to a polished, publishable OpenClaw skill. It handles:

  • 0→1: Rapid capture of fuzzy ideas → structured BRIEF → distilled skill
  • 1→N: Iterating an existing skill with new sources or structural improvements
  • N→∞: Publishing, versioning, ClawHub distribution, and ongoing maintenance

The key insight: this is not about capability, it's about workflow. Any Claw instance with this skill loaded can build production-quality skills — the process is the product.


How to Trigger This Skill

Just say something like:

New skill: [name], [1-2 sentences], [source URL (optional)]

Examples:

  • New skill: prompt-engineering, best practices from Anthropic and OpenAI
  • New skill: git-workflow, standardize my branching and PR flow, https://...
  • Skill upgrade: nova-reader, add Semantic Scholar data source

Claw will immediately enter Phase 0 — no more information needed to start.

中文用户: 新 skill:[名字],[1-2句说明],[来源URL(可选)]


Four-Phase SOP

Phase 0 · Capture(≤5 min)

Goal: Lock down the spec before any work begins.

  1. Save raw idea to inbox/<skill-name>.md
  2. Ask exactly 3 questions — no more:

- What is the target scenario / user? - Are there reference sources? (If not, Claw will search) - Publish scope: local-only / GitHub / ClawHub distribution?

  1. Generate wip/<skill-name>/BRIEF.md

Key principle: Phase 0 prevents over-engineering (LRN-003). Don't start building until the 3 questions are answered.


Phase 1 · Collect(automated)

Goal: Gather raw material without processing.

  1. web_fetch each source → save to wip/<skill-name>/raw/
  2. If no sources provided, web_search for 2–3 high-quality references
  3. Prioritize: official docs > primary blog posts > secondary analysis

Rule: At least 1 first-party source (official docs / original author's post). Raw content is saved as-is — no processing yet.


Phase 2 · Distill(core work)

Goal: Extract signal, discard noise.

  1. Read all raw/ files
  2. Write per skill-creator spec:

- SKILL.md — triggers + workflow (≤200 lines) - references/ — detailed knowledge, split by topic - scripts/ — reusable code, only if needed

  1. Mandatory verification (LRN-001): Re-fetch original source, diff against draft, check for gaps

Quality checklist:

  • [ ] Trigger words are broad enough to cover all user phrasings
  • [ ] SKILL.md has a clear "when to use" section
  • [ ] Detail lives in references/, not bloating SKILL.md
  • [ ] At least one mandatory re-read of primary source after distillation

Phase 3 · Publish

Goal: Clean, versioned, standalone repo ready for GitHub/ClawHub.

Repo Structure (Minimal)

<skill-name>/
├── SKILL.md          # Entry point (triggers + workflow)
├── README.md         # Human-facing intro — bilingual (EN + ZH)
├── CHANGELOG.md      # Version history
├── LICENSE           # MIT recommended
├── .gitignore
└── references/       # Knowledge base
    └── *.md

For script-heavy skills, add:

└── scripts/
    └── *.py

README Spec

A skill README must answer 3 questions in ≤60 seconds of reading:

  1. What problem does it solve? (1-2 sentences, no jargon)
  2. What makes it better than asking without it? (key differentiator)
  3. How do I use it? (one concrete example)

Bilingual (EN + ZH): Use two separate files for maximum clarity.

README.md       # English only — no Chinese text anywhere
README_zh.md    # Chinese only — full detail, selling points, usage

Each file includes a badge linking to the other version. This allows GitHub to render clean language-specific views and enables future ClawHub to surface the right version per locale.

ClawHub Distribution

When the user wants to publish to ClawHub:

  1. Ensure SKILL.md frontmatter has: name, version, description
  2. description must contain broad trigger phrases covering multiple phrasings
  3. LICENSE file present (MIT recommended)
  4. Tag the release: git tag v1.0.0 && git push --tags

Sync to Local Workspace

After publishing, sync to ~/.workbuddy/skills/<skill-name>/ so Claw can use it immediately:

Copy-Item -Recurse -Force "D:\WorkBuddy\<skill-name>\*" "$env:USERPROFILE\.workbuddy\skills\<skill-name>\"

Version Management

Version semantics follow Semantic Versioning adapted for skills:

MAJOR.MINOR.PATCH
Version bumpWhenExample trigger
PATCH x.x.1Typo fix, trigger word tweak, minor clarification"修复了一个例子描述不准"
MINOR x.1.0New reference source, new phase step, extended trigger coverage"加入 Anthropic 最新文档"
MAJOR 2.0.0Scope change, structural refactor, paradigm shift"从单文档改为多 reference 结构"

What warrants a MAJOR bump?

A MAJOR version (e.g. 1.x → 2.0) signals a breaking change in the skill's mental model:

  • The core SOP phases are restructured
  • The skill's scope is fundamentally redefined
  • Files are reorganized in ways that break the previous structure
  • The activation paradigm changes (e.g. from "ask anything" to "four-phase SOP")

MAJOR ≠ more content. A skill that doubles its references but keeps the same structure is still a MINOR bump.

What warrants a MINOR bump?

A MINOR version (e.g. 1.0 → 1.1 → 1.2) signals additive improvements that don't break the existing pattern:

  • New knowledge source added to references/
  • New trigger words added to frontmatter
  • New section added to SOP without restructuring existing phases
  • README improvements, badge updates

Commit message convention

feat: add [source] to references        → MINOR
fix: correct [description]              → PATCH
refactor: restructure [component]       → could be MAJOR
release: v2.0.0 - [summary]            → tag release commits

Changelog discipline

Every release must update CHANGELOG.md with:

  • Version number + date
  • Summary sentence (1 line)
  • Added / Changed / Fixed sections

Skill Iteration (1→N)

When upgrading an existing skill:

  1. Create a new branch or directly update D:/WorkBuddy/<skill-name>/
  2. Add new source to references/ with dated filename (source-YYYYMMDD.md)
  3. Update SKILL.md version field and trigger words if needed
  4. Update CHANGELOG.md
  5. Bump version (MAJOR / MINOR / PATCH per rules above)
  6. Commit with semantic message
  7. Re-sync to local workspace

Upgrade triggers: User sends new URL, user says "skill has a gap", Claw detects missing knowledge during a task execution.


Workspace Layout

D:/WorkBuddy/
├── .workspace-index.md      # Master skill status board
├── skill-factory/           # This meta-skill repo
│   ├── SKILL.md             # This file
│   ├── README.md
│   ├── CHANGELOG.md
│   ├── LICENSE
│   ├── .gitignore
│   ├── inbox/               # Raw ideas drop zone
│   └── wip/                 # Active work-in-progress
│       └── <skill-name>/
│           ├── BRIEF.md
│           ├── raw/
│           └── draft/
│
├── harness/                 # ✅ v1.2.0 — ready for GitHub
├── nova-reader/             # ✅ v1.1.0 — ready for GitHub
└── <future-skills>/

Lessons Learned (from .learnings)

IDLessonFix in SOP
LRN-001Missed content after distillation without re-reading sourcePhase 2 mandatory re-fetch
LRN-002Skill evolved in workspace, hard to publish as standalonePhase 3 independent repo
LRN-003Over-engineered before confirming real needPhase 0 three-question lock
LRN-004Research notes mixed with skill docsraw/ vs references/ separation

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

85.71%
按下载量换算984

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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