skill-creator
A toolkit for generating structured agent skill files from project requirements.
Install
mkdir -p .claude/skills/skill-creator-redwoodog && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16150" && unzip -o skill.zip -d .claude/skills/skill-creator-redwoodog && rm skill.zipInstalls to .claude/skills/skill-creator-redwoodog
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Create new skills from conversations, requirements, or by analyzing existing patterns.Key capabilities
- →Understand the need for a new skill
- →Research existing skills for patterns
- →Design the skill structure and workflow
- →Write the SKILL.md file with frontmatter and body content
- →Validate the skill file for correctness
- →Test the skill conceptually
How it works
This skill guides the creation of new skills by following a workflow that includes understanding user needs, researching existing skills, designing the skill structure, writing the SKILL.md file, and validating and testing the skill.
Inputs & outputs
When to use skill-creator
- →Define a new automated refactoring task
- →Create a skill for custom API integration
- →Format a new AI agent capability
- →Generate documentation for internal developer tools
About this skill
Skill Creator
You are an expert at creating new skills for the Hermes agent system. A skill is a SKILL.md file that provides structured instructions for the LLM to follow when performing a specific type of task.
Skill File Format
Every skill lives in its own subdirectory and follows this format:
---
name: skill-name
description: One-line description of what this skill does.
tools: comma, separated, tool, names
---
# Skill Title
Full instructions for the LLM when this skill is invoked.
Frontmatter Fields
- name: kebab-case identifier, matches the directory name
- description: One sentence. This is what the LLM reads to decide whether to invoke the skill. Make it specific and trigger-rich.
- tools: List of tools this skill needs access to. Available tools:
bash,read_file,write_file,edit_file,glob,grep,web_search,web_fetch,agent,todo_write,ask_user,schedule_cron,terminal
Body Content
The body is a system prompt that guides the LLM. It should include:
- Role statement - "You are a [role] that [does what]"
- Workflow - Numbered steps the LLM follows
- Examples - Code snippets, command templates, output formats
- Principles - Guiding rules and constraints
- Edge cases - How to handle unusual situations
Workflow for Creating a Skill
Step 1: Understand the Need
Ask the user:
- What task should this skill handle?
- When should it be triggered? (What phrases or situations?)
- What tools does it need?
- Are there existing skills that do something similar?
Step 2: Research Existing Skills
find /path/to/skills -name "SKILL.md" | head -30
Read related skills to understand patterns, formatting conventions, and avoid duplication.
Step 3: Design the Skill
Plan the skill structure:
- What is the step-by-step workflow?
- What commands or code patterns does it use?
- What are the common failure modes?
- What should the LLM do vs. what should it ask the user?
Step 4: Write the Skill
Create the directory and SKILL.md file:
mkdir -p /path/to/skills/category/skill-name
Write the SKILL.md following the format above. Key quality criteria:
Description must be specific:
- BAD: "Helps with code"
- GOOD: "Create clean git commits with descriptive messages based on staged or working changes."
Instructions must be actionable:
- BAD: "Review the code"
- GOOD: "Run
git diff HEADto see all changes. For each changed file, read the full file to understand context."
Include real command templates:
- BAD: "Use git to check status"
- GOOD:
bash\ngit status --porcelain\ngit diff --stat\n
Handle errors and edge cases:
- BAD: (nothing about errors)
- GOOD: "If no test runner is detected, ask the user what command runs tests."
Step 5: Validate
Check the skill file:
- Frontmatter parses correctly (valid YAML between
---markers) - Tools listed are all valid tool names
- Instructions are complete - could another LLM follow them without your help?
- No placeholders or TODOs left in the content
Step 6: Test Conceptually
Walk through the skill as if you were the LLM receiving it:
- Is Step 1 clear enough to start without ambiguity?
- Does each step lead naturally to the next?
- Are there decision points that need if/else guidance?
- Is the output format specified?
Principles for Good Skills
- Self-contained - The skill should include everything the LLM needs. Don't assume prior knowledge.
- Opinionated - Make decisions. "Use X approach" is better than "You could use X or Y."
- Tool-aware - Only reference tools that exist in the system. Don't tell the LLM to use tools it doesn't have.
- Outcome-focused - Define what "done" looks like. The LLM should know when the task is complete.
- Defensive - Include guidance for when things go wrong (missing files, failed commands, ambiguous inputs).
When not to use it
- →When the skill description is not specific
- →When instructions are not actionable
- →When real command templates are not included
Limitations
- →Skill description must be specific
- →Instructions must be actionable
- →Must include real command templates
How it compares
This skill provides a structured, step-by-step process for skill creation, ensuring consistency, actionability, and adherence to format, unlike ad-hoc skill definition.
Compared to similar skills
skill-creator side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| skill-creator (this skill) | 0 | 4mo | Review | Intermediate |
| prompt-optimizer | 43 | 6mo | No flags | Beginner |
| context-compression | 13 | 3mo | Review | Advanced |
| learner | 2 | 3mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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