Skill Factory

A meta-skill for creating, iterating, and publishing OpenClaw skills from scratch. Use this skill when the user wants to: build a new skill from an idea or U...

Security Scan

Skill Factory is an instruction-only meta-skill whose requests and instructions are coherent with its purpose (creating and publishing other skills); no code or unusual credential requests are present, but review outputs and publishing steps before giving it access to your accounts or private data.

Purpose & Capability

The skill claims to be a meta-skill for creating, iterating, and publishing OpenClaw skills and is implemented as instruction-only content that describes collecting web sources, writing local SKILL.md and repo files, and publishing. There are no unrelated environment variables, binaries, or install steps requested. Minor documentation inconsistencies exist (README/CHANGELOG reference different GitHub repo owners/paths and SKILL.md frontmatter version differs slightly from registry metadata), but these look like documentation hygiene issues rather than functional mismatches.

Instruction Scope

Runtime instructions describe agent actions such as web_fetch/web_search, saving raw content to inbox/wip/<skill>/raw/, generating SKILL.md and references/, and syncing published files to a local skills directory. These actions are consistent with a skill-builder. The SKILL.md examples include filesystem copy commands that reference the user profile ($env:USERPROFILE) and Windows PowerShell Copy-Item; the skill does not instruct collecting shell history or secrets. Note: web_fetch will download external content (expected), so users should avoid directing the skill at private endpoints or embedding secrets in source URLs.

Install Mechanism

Instruction-only skill with no install spec or code files — lowest-risk install surface. README suggests optional ways to install from ClawHub or by git-cloning a GitHub repo; those are normal and not executed automatically by this skill.

Credentials

The skill declares no required environment variables, no primary credential, and no required config paths. It references operations (git tag, git push, ClawHub distribution) that would require GitHub or ClawHub credentials if the user chooses to publish, but the skill does not request or hardcode credentials itself — this is proportionate. The SKILL.md example references $env:USERPROFILE in a copy command (sample only).

Persistence & Privilege

always:false and model invocation is allowed (normal). The skill's workflow includes writing files into local workspaces (~/.workbuddy or ~/.claw/skills), which is expected for a publishable skill factory. It does not request permanent platform-wide privileges or modify other skills' configs.

Assessment

This skill is internally consistent with its stated goal and is instruction-only (no code to execute directly), but take these practical steps before using it: - Review generated SKILL.md/BRIEF.md/README files before running any publish or git push commands. The skill will create and write files into your skills workspace; inspect them first. - Publishing to GitHub or ClawHub requires credentials (git push, claw skill publish) — the skill does not request them directly; only perform publishing if you trust the generated content and the target repo. - The skill's collection phase (web_fetch/web_search) downloads external content. Avoid pointing it at internal or private URLs that contain secrets. - Note minor docs inconsistencies: README/CHANGELOG reference different GitHub repo paths/owners and there is a small version string mismatch in frontmatter — consider which upstream repository you will trust before cloning. - If you want extra safety, run the workflow in an isolated account or VM and confirm outputs before integrating into your main skill workspace.

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.

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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）]

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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?
3. 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.

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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.

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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
3. 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

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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>\"

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Version Management

Version semantics follow Semantic Versioning adapted for skills:

MAJOR.MINOR.PATCH

Version bump	When	Example trigger
PATCH x.x.1	Typo fix, trigger word tweak, minor clarification	"修复了一个例子描述不准"
MINOR x.1.0	New reference source, new phase step, extended trigger coverage	"加入 Anthropic 最新文档"
MAJOR 2.0.0	Scope 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

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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.

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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>/

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Lessons Learned (from .learnings)

ID	Lesson	Fix in SOP
LRN-001	Missed content after distillation without re-reading source	Phase 2 mandatory re-fetch
LRN-002	Skill evolved in workspace, hard to publish as standalone	Phase 3 independent repo
LRN-003	Over-engineered before confirming real need	Phase 0 three-question lock
LRN-004	Research notes mixed with skill docs	raw/ vs references/ separation