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Skill Creator

Community
HazAT
skill-creator

Create new agent skills following the Agent Skills specification. Use when asked to "create a skill", "add a new skill", "write a skill", "make a skill", "build a skill", or scaffold a new skill with SKILL.md. Guides through requirements, planning, writing, registration, and verification.

Overview

PublisherHazAT
Repositorypi-config
Skill nameskill-creator
Stars
450
Forks
44
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by HazAT on GitHub. Read the source before you install it.

Installation

Install the Skill Creator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HazAT/pi-config.git /tmp/pi-config
mkdir -p .claude/skills
cp -r /tmp/pi-config/skills/skill-creator .claude/skills/skill-creator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Creator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skill Creator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skill Creator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Create a New Skill

Guide the user through creating a new agent skill following the Agent Skills specification. Follow each step in order.

Step 1: Understand the Skill

Gather requirements before writing anything.

Ask the user:

  1. What should this skill do? (one sentence)
  2. When should an agent use it? (trigger phrases users would say)
  3. What tools does the skill need? (Read, Grep, Glob, Bash, Task, WebFetch, etc.)
  4. Where should the skill live? (which plugin or directory)

Determine the skill name:

  • Lowercase letters, digits, and hyphens only (a-z, 0-9, -)
  • 1-64 characters; must not start or end with -; no consecutive hyphens (--)
  • Descriptive and unique among existing skills
  • Prefer action-oriented names: processing-pdfs, fix-issue, code-review
  • Check the target skills directory to avoid name collisions

Choose a complexity tier:

TierStructureUse When
SimpleSKILL.md onlySelf-contained instructions under ~200 lines
With referencesSKILL.md + references/Domain knowledge that agents load conditionally
With scriptsSKILL.md + scripts/Workflow automation needing Python scripts
FullAll of the aboveComplex skills with automation and domain knowledge

Read ${CLAUDE_SKILL_ROOT}/references/design-principles.md for guidance on keeping skills focused and concise.

Step 2: Plan the Skill

Analyze how each use case would be executed from scratch. Identify what reusable resources would help when executing these tasks repeatedly.

For each concrete example, ask:

  1. What code would be rewritten every time? → candidate for scripts/
  2. What documentation is needed to inform decisions? → candidate for references/
  3. What templates or assets are used in output? → candidate for assets/

Example analysis:

  • "Rotate a PDF" → rotating requires rewriting the same code → scripts/rotate_pdf.py
  • "Query BigQuery metrics" → need table schemas each time → references/schema.md
  • "Build a frontend app" → same boilerplate HTML/React → assets/hello-world/

Step 3: Study Existing Skills

Before writing, study 1-2 existing skills that match the chosen tier. Look for skills in the target repository or plugin to understand local conventions.

Read ${CLAUDE_SKILL_ROOT}/references/skill-patterns.md for concrete examples of each tier.

Also read CLAUDE.md (or AGENTS.md) at the repository root for repo-specific conventions that the skill should follow.

Step 4: Write the SKILL.md

Create <skill-directory>/<name>/SKILL.md.

Frontmatter

The YAML frontmatter must be the first thing in the file. No comments or blank lines before ---.

yaml
---
name: <skill-name>
description: <what it does>. Use when <trigger phrases>. <key capabilities>.
---

Required fields:

  • name — must match the directory name exactly
  • description — up to 1024 chars, no angle brackets (< or >); include trigger keywords that help agents match user intent

Optional fields:

  • allowed-tools — comma-separated list (e.g., Read, Grep, Glob, Bash); omit to allow all tools
  • license — license name or path (add when vendoring external content)
  • metadata — arbitrary key-value mapping for additional metadata
  • compatibility — environment requirements (max 500 chars); most skills don't need this

For Claude Code-specific fields (argument-hint, disable-model-invocation, context, etc.), read ${CLAUDE_SKILL_ROOT}/references/claude-code-extensions.md.

Description Guidelines

The description is the primary trigger mechanism — it determines when agents activate the skill. All "when to use" information belongs here, not in the body.

Write in third person:

  • Good: "Processes Excel files and generates reports. Use when..."
  • Bad: "I can help you process Excel files" or "You can use this to..."

Include natural trigger phrases:

yaml
# Good — specific triggers users would actually say
description: Security code review for vulnerabilities. Use when asked to "security review", "find vulnerabilities", "check for security issues", "audit security".

# Bad — too vague, no trigger phrases
description: A helpful skill for code quality.

Pattern: <What it does>. Use when <trigger phrases>. <Key capabilities>.

Body Guidelines

Write the body in imperative voice — these are instructions, not documentation.

DoDon't
"Read the file and extract...""This skill reads the file and extracts..."
"Report only HIGH confidence findings""The agent should report only HIGH confidence findings"
"Ask the user which option to use""You may want to ask the user..."

Structure:

  1. Start with a one-line summary of what the skill does
  2. Organize steps with ## Step N: Title headings
  3. Use tables for decision logic and mappings
  4. Include concrete examples of expected output
  5. End with validation criteria or exit conditions

For workflow and output patterns, read:

  • ${CLAUDE_SKILL_ROOT}/references/workflow-patterns.md — sequential workflows, feedback loops, plan-validate-execute
  • ${CLAUDE_SKILL_ROOT}/references/output-patterns.md — template, examples, and structured data patterns

Size limits:

  • Keep SKILL.md under 500 lines (< 5000 tokens recommended)
  • If approaching the limit, move reference material to references/ files
  • Load reference files conditionally based on context (not all at once)

Use consistent terminology — pick one term for each concept and stick with it throughout. Don't alternate between "API endpoint", "URL", "route", and "path".

Attribution

If the skill is based on or adapted from external sources, add an HTML comment after the frontmatter closing ---:

markdown
---
name: example
description: ...
---

<!--
Based on [Original Name] by [Author/Org]:
https://github.com/example/original-source
-->

Step 5: Create Supporting Files

What to Include

Only include files that directly support the skill's function.

What NOT to Include

Do not create extraneous documentation or auxiliary files:

  • README.md, INSTALLATION_GUIDE.md, QUICK_REFERENCE.md, CHANGELOG.md

A skill should contain only what an agent needs to do the job. Not setup procedures, not user-facing docs, not development history.

References (references/)

Use for domain knowledge the agent loads conditionally.

<name>/
├── SKILL.md
└── references/
    ├── topic-a.md
    └── topic-b.md

Reference from SKILL.md with:

markdown
Read `${CLAUDE_SKILL_ROOT}/references/topic-a.md` for details on [topic].

Guidelines:

  • Keep each reference file focused on one topic
  • Keep references one level deep from SKILL.md (no nested reference chains)
  • For files over 100 lines, add a table of contents at the top
  • For files over 10k words, include grep search patterns in SKILL.md
  • Information should live in either SKILL.md or references, not both

Scripts (scripts/)

Use for workflow automation that benefits from structured Python.

<name>/
├── SKILL.md
└── scripts/
    └── do_thing.py

Script requirements:

  • Always use uv run to execute: uv run ${CLAUDE_SKILL_ROOT}/scripts/do_thing.py
  • Add PEP 723 inline metadata for dependencies:
python
# /// script
# requires-python = ">=3.12"
# dependencies = ["requests"]
# ///
  • Output structured JSON for agent consumption
  • Run from the repository root, not the skill directory
  • Document the script's interface in SKILL.md (arguments, output format)
  • Handle errors explicitly — don't punt to the agent

Assets (assets/)

Use for static files used in the skill's output (templates, images, boilerplate code, fonts). These are not loaded into context — they're copied or used directly.

LICENSE

Include a LICENSE file in the skill directory when vendoring content with specific licensing requirements.

Step 6: Validate the Skill

Run the validation script to catch issues early:

bash
uv run ${CLAUDE_SKILL_ROOT}/scripts/quick_validate.py <path/to/skill-directory>

The script checks frontmatter format, required fields, naming rules, and common mistakes. Fix any errors and re-run until validation passes.

Alternatively, use the upstream validation tool:

bash
skills-ref validate <path/to/skill-directory>

Step 7: Register the Skill

Registration steps vary by repository. Check the repository's CLAUDE.md or README.md for specific instructions.

  1. Verify directory-name match — confirm the directory name matches the name field in SKILL.md frontmatter exactly
  2. Update documentation — add the skill to any skills index or table in README.md
  3. Update permissions — if the repo has .claude/settings.json, add Skill(<plugin>:<name>) to the permissions.allow array
  4. Check CLAUDE.md — read the repository's CLAUDE.md for any additional registration steps specific to that project

Step 8: Verify

Run through this checklist before finishing:

Frontmatter

  • name matches directory name
  • name uses only lowercase letters, digits, hyphens (no leading/trailing/consecutive hyphens)
  • description is under 1024 characters, no angle brackets
  • description is in third person and includes trigger keywords
  • All "when to use" info is in description, not in body
  • No content before the opening ---

Content

  • SKILL.md is under 500 lines
  • Written in imperative voice
  • Steps are numbered and clear
  • Examples of expected output included
  • Consistent terminology throughout
  • Reference files loaded conditionally (not unconditionally)
  • No extraneous files (README.md, CHANGELOG.md, etc.)

Registration

  • Directory name matches frontmatter name
  • Skill added to repo documentation (README or equivalent)
  • Permissions updated (if applicable)
  • Any repo-specific registration steps completed (check CLAUDE.md)

Scripts (if applicable)

  • Uses uv run ${CLAUDE_SKILL_ROOT}/scripts/...
  • Has PEP 723 inline metadata
  • Outputs structured JSON
  • Handles errors explicitly
  • Documented in SKILL.md

Validation

  • uv run ${CLAUDE_SKILL_ROOT}/scripts/quick_validate.py passes
  • Tested with a real usage scenario

Report any issues found and fix them before completing.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Skill Creator AI skill do?

Create new agent skills following the Agent Skills specification. Use when asked to "create a skill", "add a new skill", "write a skill", "make a skill", "build a skill", or scaffold a new skill with SKILL.md. Guides through requirements, planning, writing, registration, and verification.

Why use Skill Creator on TypingMind?

Because you install it once and use it with any model. Skill Creator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skill Creator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HazAT/pi-config/tree/main/skills/skill-creator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Skill Creator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skill Creator?

As many as you like. As long as a model supports skills, you can use Skill Creator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skill Creator AI skill free?

Yes. It is published on GitHub by HazAT under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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