skill-creator
Skill108 starsChanged 8 months agoMITView on GitHub
Meta-skill that generates new Claude Code skills. Given a domain description, it creates a complete SKILL.md + references/ structure following AgenticWorkflow conventions. Use when asked to "create a skill", "make a new skill", or "generate skill for X".
189 other projects use a version of this.
Adopted by
Most recently taken up by
- SebastienDegodez/copilot-instructionstheir own version, first seen Nov 8, 2026
- idavidov13/agentic-playwrighttheir own version, first seen Nov 8, 2026
- HughYau/AcademicForgetheir own version, first seen Nov 8, 2026
- Ar9av/obsidian-wikitheir own version, first seen Nov 8, 2026
- rvdbreemen/OTGW-firmwaretheir own version, first seen Nov 8, 2026
- scenario-labs/skillstheir own version, first seen Nov 7, 2026
Used with
Projects with it also use taskflow-inbox-triage, mermaid-diagram-generator and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
AtomicBot-aiSkilltaskflow-inbox-triage
Also in 6 projects that use this
shalombSkillmermaid-diagram-generator
Guide on creating and editing Mermaid charts safely. Use when asked to draw a diagram, flowchart, or architecture chart. Triggers on: 'mermaid', 'diagram', 'flowchart', 'visualize'.
Also in 5 projects that use this
naman10parikhSkillecosystem-reference
Quick-access directory of Claude Code ecosystem repos, skills, plugins, MCPs, and patterns. Use when improving the harness.
Also in 5 projects that use this
naman10parikhSkillfractal-delegation
Also in 5 projects that use this
Liang-MHSkillstock_analysis
获取 A 股、基金和港股的实时行情和技术分析数据
Also in 5 projects that use this
nicepkgSkillcommunity-led-growth
Expert in community-led growth (CLG) - leveraging user communities to drive acquisition, retention, and expansion. Covers building developer communities, user groups, ambassador programs, and turning customers into advocates. Knows the difference between community as a feature vs community as a growth engine, and how to measure community ROI. Use when "community-led, CLG, ambassador program, champion program, user community, developer community, word of mouth, user group, " mentioned.
Also in 5 projects that use this
- +6 more from naman10parikh
Other versions189 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 189
- moltbot/clawdbot★ 394ksame name
- steipete/warelay★ 394ksame name
- steipete/clawdis★ 394ksame name
- moltbot/moltbot★ 394ksame name
- clawdbot/clawdbot★ 394ksame name
- openclaw/openclaw★ 394ksame name
- molt-bot/clawdbot★ 391ksame name
- anthropics/skills★ 189ksame name
- openai/codex★ 134ksame name
- google-gemini/gemini-cli★ 109ksame name
179 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository7 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/agenticworkflow.mdcCursor rule
- doctoral-writingSkill
- subagent-creatorSkill
- workflow-generatorSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 185 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 41
Ask the user a maximum of 4 questions (P4 rule), each with up to 3 choices.
- Distinctive: line 42
If the domain is clear enough, proceed without questions.
- Very specific: line 113
Create supporting documents in references/:
- Distinctive: line 120
Verify the generated skill:
- Distinctive: line 130
Must PASS all 5 rules (FS-1~FS-5).
“Common” is measured: kept by at least 6 in 10 of the 185 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Skill Creator — Meta-Skill for Generating Claude Code Skills
A meta-skill that produces new skill packages. It analyzes the target domain, designs the skill structure, and generates all required files following AgenticWorkflow's DNA inheritance patterns.
When to Use
- User asks to create a new skill for a specific domain
- User wants to automate a repeatable workflow as a skill
- System needs to generate skills for thesis workflow agents
Inherited DNA
This meta-skill inherits the AgenticWorkflow genome. As a skill that generates other skills, it must itself embody the DNA it enforces.
| DNA Component | Expression in skill-creator |
| Absolute Criteria 1 (Quality) | Generated skills are evaluated solely on output quality, not speed or token cost |
| Absolute Criteria 2 (SOT) | Generated skills must define their SOT pattern; skill-creator validates this |
| Absolute Criteria 3 (CCP) | Generated skills include CCP contextualization; CAP-1~4 anchored to domain |
| English-First | All generated skill instructions are in English; user-facing triggers may be bilingual |
| P1 Compliance | Generated skills must include deterministic validation scripts |
| Quality Gates | Generated skills reference L0-L2 quality layers appropriate to their domain |
Generation Protocol
Step 1: Domain Analysis
Analyze the target domain:
- What is the primary output of this skill?
- What inputs does it require?
- What quality criteria apply?
- Which tasks are deterministic (P1) vs. semantic (LLM)?
Ask the user a maximum of 4 questions (P4 rule), each with up to 3 choices. If the domain is clear enough, proceed without questions.
Step 2: Skill Architecture Design
Design the skill structure:
.claude/skills/{skill-name}/
├── SKILL.md ← Main skill file (WHY + HOW)
└── references/ ← Supporting documents (WHAT/VERIFY)
├── {domain}-guide.md ← Domain-specific guidance
├── {domain}-checklist.md ← Quality checklist
└── {domain}-examples.md ← Before/after examples (if applicable)Step 3: Generate SKILL.md
The generated SKILL.md must follow this template:
---
name: {skill-name}
description: {one-line description for skill matching}
# Optional — context isolation and agent type (see Selection Criteria below)
# context: fork # omit for inline (default), add for isolated execution
# agent: general-purpose # only with context: fork — Explore | Plan | general-purpose | <custom-agent>
---
# {Skill Title}
{Brief description of what the skill does.}
## Inherited DNA
{Absolute criteria contextualized for this domain}
## Protocol
{Step-by-step execution protocol}
## Quality Gates
{Domain-specific quality criteria}
## P1 Enforcement
{List of deterministic validations, if any}context: fork + agent Selection Criteria
These optional frontmatter fields control where and how the skill executes. Default is inline (no field needed).
| Criterion | Inline (default) | Fork |
| User interaction needed (Q&A, HITL) | ✅ | ❌ |
| Works within ongoing conversation context | ✅ | ❌ |
| Independent analysis/transformation | ❌ | ✅ |
| Execution details would pollute main context | ❌ | ✅ |
| SOT access | Direct | Read-only (file output → Orchestrator records in SOT) |
Constraints — fork MUST NOT be used when:
- Skill writes to SOT directly (violates Absolute Criteria 2 single-writer)
- Skill requires sequential quality gate passage (L0→L1→L1.5→L2) with main context visibility
- Skill needs Bash but the specified agent lacks Bash tool access
- Skill is part of the main orchestration flow (router, resume, HITL gates)
agent field specifies which agent type runs the forked context. Only meaningful with context: fork:
Explore— read-only codebase search (haiku model)Plan— architecture research, read-onlygeneral-purpose— full tool access, multi-step tasks{custom-agent}— any agent defined in.claude/agents/(inherits that agent's model, tools, behavior)
Step 4: Generate Reference Files
Create supporting documents in references/:
- Domain guide: Detailed domain knowledge and best practices
- Checklist: Verification items for quality assurance
- Examples: Concrete examples of good/bad outputs (when applicable)
Step 5: Validate Generated Skill
Verify the generated skill:
- SKILL.md has valid frontmatter (name, description; optional: context, agent)
- Inherited DNA section present with all applicable genome components
- Protocol has clear, numbered steps
- Quality gates defined
- References directory populated
- No hardcoded paths (uses relative references)
- Language: internal instructions in English, user-facing in Korean
- Fork Safety P1 Validation (if
context: forkin frontmatter): Runpython3 .claude/hooks/scripts/validate_fork_safety.py --file <generated-SKILL.md> --project-dir <project-root>Must PASS all 5 rules (FS-1~FS-5). FAIL → fix violations before proceeding to Step 6.
Step 6: Register Skill
Inform the user:
- Skill location:
.claude/skills/{skill-name}/ - How to trigger it (matching patterns from description)
- Any required setup (dependencies, configuration)
Language Rules
- SKILL.md internal instructions: English (for AI performance)
- SKILL.md description (frontmatter): Korean (for user-facing matching)
- Reference files: English (domain knowledge for AI consumption)
- Generated output for users: Korean (user-facing reports)
Quality Checklist
- Generated skill follows AgenticWorkflow conventions
- DNA inheritance is complete (not just referenced)
- Steps are concrete and actionable
- P1 tasks identified and separated from LLM tasks
- No placeholder content — all sections are substantive
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

