Agent skill

Skill Creator

by ghbalf in ghbalf/freecad-ai

Create new FreeCAD AI skills, modify existing skills, and iteratively improve them.

LGPL-2.1Auto-check passedAgent Workflows

Install Skill Creator

skills CLI
$ npx skills add ghbalf/freecad-ai --skill skill-creator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ghbalf/freecad-ai skill-creator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ghbalf/freecad-ai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skill-creator .claude/skills/skill-creator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skill-creator
GitHub stars
550
Token cost
~2.7k tokens
SKILL.md length
1,248 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
LGPL-2.1

At a glance

Create new FreeCAD AI skills, modify existing skills, and iteratively improve them.

  • Works in 6 steps: Capture intent → Interview and research → Choose a name → …
  • Users want to create a skill from scratch
  • SKILL.md covers Communicating with the user, Creating a skill, Testing and improving and Improving an existing skill, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Skill Creator is an agent skill from ghbalf/freecad-ai. Create new FreeCAD AI skills, modify existing skills, and iteratively improve them. Use when users want to create a skill from scratch, update or optimize an existing skill, capture a workflow as a reusable skill, or improve an existing skill's instructions. Also trigger when the user says "turn this into a skill", "make a skill for X", "save this as a command", or similar.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Skill authoring. The repository describes itself as: AI-powered assistant workbench for FreeCAD — generate 3D models from natural language.

When your agent uses it

  • Users want to create a skill from scratch
  • Optimize an existing skill
  • Capture a workflow as a reusable skill
  • Improve an existing skills instructions

Example prompts

  • “s instructions. Also trigger when the user says”
  • “make a skill for X”
  • “save this as a command”
  • “/skill-creator”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Capture intent
  2. Interview and research
  3. Choose a name
  4. Write the SKILL.md
  5. Write handler.py (optional)
  6. Save the files

What it can do on your machine

Read from SKILL.md and the folder at commit 5ef1e2d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Creator loads about 2.7k tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 1,248 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ghbalf/freecad-ai at commit 5ef1e2d, republished under its LGPL-2.1 licence (© ghbalf). 1,248 words, ~2,666 tokens.

Download SKILL.mdSave it as .claude/skills/skill-creator/SKILL.md (or your agent's skills folder).
name
skill-creator
description
Create new FreeCAD AI skills, modify existing skills, and iteratively improve them. Use when users want to create a skill from scratch, update or optimize an existing skill, capture a workflow as a reusable skill, or improve an existing skill's instructions. Also trigger when the user says "turn this into a skill", "make a skill for X", "save this as a command", or similar.

Skill Creator

A skill for creating new FreeCAD AI skills and iteratively improving them.

At a high level, the process goes like this:

  • Understand what the user wants the skill to do
  • Interview for details — parameters, edge cases, construction approach
  • Write a draft of the skill (SKILL.md + optional handler.py)
  • Test it by running the /command and evaluating the result
  • Improve based on what worked and what didn't
  • Repeat until the user is satisfied

Your job is to figure out where the user is in this process and help them move forward. Maybe they say "I want a skill for X" — help them scope it, write the draft, and test it. Or maybe they already have a skill that needs fixing — jump straight to the improvement loop.

Be flexible. If the user says "just write it, I'll test it myself", do that. If they want to iterate 5 times, do that too.

Communicating with the user

FreeCAD AI users range from experienced CAD engineers to hobbyists who just discovered parametric modeling. Pay attention to context cues — if they use terms like "involute" and "datum plane", match that level. If they say "I want to make a box thing with holes", keep things simple.


Creating a skill

Step 1: Capture intent

Start by understanding what the user wants. The current conversation may already contain a workflow worth capturing (e.g., they say "turn this into a skill"). If so, extract what you can from the conversation — the tools used, the sequence of steps, corrections the user made, dimensions and parameters observed. The user may need to fill gaps, and should confirm before you proceed.

Ask (skip questions they already answered):

  1. What should the skill do? — e.g., "generate a mounting bracket", "create a gear train"
  2. What parameters should the user provide? — dimensions, counts, materials, tolerances
  3. When should someone use this? — what would they type to invoke it?
  4. What's the construction approach? — which FreeCAD operations, in what order?
  5. Are there edge cases? — minimum wall thickness, maximum overhang angle, material constraints
  6. Should it have a Python handler? — for skills that need deterministic logic (calculations, lookups) rather than just LLM instructions
Step 2: Interview and research

Proactively ask about things the user might not think of:

  • Standard dimensions — are there industry standards to reference? (bolt sizes, bearing bores, thread pitches)
  • FreeCAD pitfalls — coplanar boolean failures, unclosed sketches, Revolution crashes with full-circle profiles
  • Parameter validation — what ranges are reasonable? What breaks?
  • Construction order — does the workflow depend on features being created in a specific sequence?

If the current document has relevant objects, inspect them with get_document_state and measure to understand the context.

Step 3: Choose a name

Pick a short, hyphenated name based on what the skill does. Confirm with the user. The skill will live at: ~/.config/FreeCAD/FreeCADAI/skills/<name>/ The user invokes it with /<name>.

Step 4: Write the SKILL.md
Anatomy of a skill
skill-name/
├── SKILL.md          (required — frontmatter `name` + `description`, then instructions)
├── handler.py        (optional, FreeCAD AI only — deterministic execute(args) handler)
├── references/       (optional — docs the model reads on demand, subfolders allowed)
│   ├── dimensions.md
│   └── materials.md
├── scripts/          (optional — Python scripts run with run_skill_script)
└── assets/           (optional — templates/data files the scripts open via __file__)

This is the open Agent Skills layout, so the same folder also works in Claude Code, Codex or Gemini CLI. Start SKILL.md with frontmatter whose name equals the folder name:

---
name: skill-name
description: "What it does and when to use it, in one or two sentences."
---

Quote the description: other harnesses parse it as strict YAML, where an unquoted : breaks it. Link files with relative Markdown links, e.g. [thread table](references/thread-tables.md); the model loads them with use_skill(name=..., resource="references/thread-tables.md").

Progressive disclosure

Skills use a layered loading system:

  1. Name + first line — always visible in the skills list (~10 words)
  2. SKILL.md body — loaded when the skill is invoked (<200 lines ideal)
  3. References — loaded on demand when the skill tells the LLM to read them

Keep SKILL.md under 200 lines. If you need more detail (dimension tables, material properties, multi-variant instructions), put it in references/ and point to it from SKILL.md:

markdown
For standard metric thread dimensions, read `references/thread-tables.md`.
SKILL.md structure

A good SKILL.md includes:

  • Title and one-line description
  • Parameters the user should provide (with sensible defaults)
  • Step-by-step construction instructions using the tool calling system
  • Important notes — gotchas, tolerances, material considerations
  • Reference data — standard dimensions, lookup tables (or pointers to reference files)
Writing style

Explain the why behind instructions, not just the what. The LLM is smart — if it understands the reasoning, it can adapt to situations the instructions don't cover explicitly.

Instead of:

markdown
ALWAYS use offset=H on the pocket sketch. NEVER pocket from z=0.

Write:

markdown
Place the pocket sketch at offset=H (top face of the solid). Pocketing from z=0
creates a hollow that opens upward with no floor — the pocket cuts from the sketch
plane downward into the solid, so starting from the top gives you a proper floor
at the bottom.

More guidance:

  • Be specific about FreeCAD operations — name the exact tool, feature type, and property names
  • Include default values — so the user can invoke with minimal arguments
  • Use the tool names — create_sketch, pad_sketch, pocket_sketch, etc. The LLM knows all 33 tools
  • Warn about pitfalls — but explain why they're pitfalls, not just "don't do this"
Show full SKILL.md (504 more words)Show less
Step 5: Write handler.py (optional)

If the skill benefits from a Python handler, write one with an execute(args) function:

python
def execute(args):
    """
    Args:
        args: string with the user's arguments after the /command

    Returns:
        dict with one of:
          {"inject_prompt": "text"} — inject into LLM prompt
          {"output": "text"} — display directly to user
          {"error": "text"} — show error
    """

Use a handler when the skill needs:

  • Calculations (gear tooth profiles, thread geometry, stress analysis)
  • Lookup tables that are easier in Python than in prose
  • File I/O (reading templates, writing config)
  • Validation of user parameters before sending to the LLM
Step 6: Save the files

Use the execute_code tool to create the skill directory and write the files:

python
import os
skill_dir = os.path.expanduser("~/.config/FreeCAD/FreeCADAI/skills/<name>")
os.makedirs(skill_dir, exist_ok=True)

with open(os.path.join(skill_dir, "SKILL.md"), "w") as f:
    f.write(skill_md_content)

# Optional:
with open(os.path.join(skill_dir, "handler.py"), "w") as f:
    f.write(handler_content)

Tell the user the skill is ready and they can invoke it with /<name>.


Testing and improving

After writing the draft, test it. Come up with 2–3 realistic invocations — the kind of thing a real user would type:

/bracket 80x40mm, 4 mounting holes M4, 3mm thick aluminum
/bracket 30x20mm, 2 holes M3
/bracket — just use defaults

Share them with the user: "Here are a few test cases I'd like to try. Do these look right, or would you change any?"

Then run them one at a time. After each run:

  • Check the result with get_document_state and measure
  • Note what worked and what didn't
  • Ask the user for feedback
How to think about improvements
  1. Generalize from the feedback. The skill will be used many times with different parameters. Don't overfit to the test cases — if a fix only works for one specific set of dimensions, it's probably too narrow. Think about what principle the fix represents and express that in the instructions.

  2. Keep the prompt lean. Remove instructions that aren't pulling their weight. If the LLM is spending time on unnecessary steps, cut them. Read the actual tool call sequence to see where time is wasted.

  3. Explain the why. If you find yourself writing ALWAYS or NEVER in all caps, that's a sign the instruction needs a reason, not more emphasis. Explain why the thing matters and the LLM will follow through more reliably.

  4. Look for repeated patterns. If every test run independently arrives at the same multi-step workaround, that's a signal the skill should include that approach explicitly — or bundle it in a handler.

The iteration loop
  1. Improve the skill based on feedback
  2. Re-run the test cases
  3. Check results, ask user for feedback
  4. Repeat until the user is happy or improvements plateau

Improving an existing skill

If the user already has a skill they want to improve:

  1. Read the current SKILL.md
  2. Ask what's not working — specific failures, edge cases, quality issues
  3. Run it on a few test cases to reproduce the problems
  4. Apply improvements following the same principles above
  5. Re-test and iterate

Reference files

For skills that need reference data (dimension tables, material properties, standard specifications), create a references/ directory alongside SKILL.md. Keep each reference file focused on one topic and under 300 lines. Include a brief table of contents at the top of long files.

Example structure for a fastener skill:

fastener/
├── SKILL.md
└── references/
    ├── metric-bolts.md      # M2–M24 dimensions
    ├── imperial-bolts.md    # #2–1" dimensions
    └── materials.md         # Strength grades, torque specs

Reference files may live in subfolders (references/metric/m3.md). A script in scripts/ runs inside FreeCAD like a command-line program: it sees __name__ == "__main__", sys.argv, and its own __file__, so it can open ../assets/... next to it. Use sys.exit(1) to report failure.

© ghbalf, LGPL-2.1. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/skill-creator of ghbalf/freecad-ai.

Open the folder on GitHubat commit 5ef1e2d

Compare with similar skills

Skill Creator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Creator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Creator this skillghbalf/freecad-ai550—~2.7kAutomated safety check: PassLGPL-2.1
Skill CreatorAzure/azqr79589 repos~8.2kAutomated safety check: PassApache-2.0
Claude Code Skill Developer Guidediet103/claude-code-infrastructure-showcase10k11 repos~3.5kAutomated safety check: PassMIT
Darwin Skill Optimizeralchaincyf/darwin-skill6.2k1 repos~4.7kAutomated safety check: PassMIT
Claude Code Command Developmentanthropics/claude-plugins-official38k10 repos~4.8kAutomated safety check: PassApache-2.0
Claude Code Plugin Structureanthropics/claude-plugins-official38k10 repos~3.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Skill Creator

What does Skill Creator do?

Create new FreeCAD AI skills, modify existing skills, and iteratively improve them. Skill Creator is an agent skill from ghbalf/freecad-ai. Create new FreeCAD AI skills, modify existing skills, and iteratively improve them.

When should I use Skill Creator?

Skill Creator fits situations like: users want to create a skill from scratch; optimize an existing skill; capture a workflow as a reusable skill; improve an existing skills instructions.

How do I install Skill Creator in Claude Code?

Run `npx skills add ghbalf/freecad-ai --skill skill-creator -a claude-code`. Or copy the skill folder (skills/skill-creator in ghbalf/freecad-ai) into .claude/skills/skill-creator in your project. Claude Code loads it when a task matches its description.

How do I install Skill Creator in Codex?

Run `npx skills add ghbalf/freecad-ai --skill skill-creator -a codex`. Or copy the skill folder (skills/skill-creator in ghbalf/freecad-ai) into .agents/skills/skill-creator in your project. Codex loads it when a task matches its description.

Can I use Skill Creator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ghbalf/freecad-ai --skill skill-creator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-creator, .gemini/skills/skill-creator, .github/skills/skill-creator and .opencode/skills/skill-creator in your project.

What does Skill Creator need to run?

SKILL.md names no scripts, command-line tools or credentials: Skill Creator is instructions for the agent only. Our summary lists: Python 3.

Does Skill Creator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skill Creator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skill Creator use?

Skill Creator is published under the LGPL-2.1 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Creator use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Skill Creator?

Skills that share tags, products or a category with Skill Creator: Skill Creator (Azure/azqr, 795 stars), Claude Code Skill Developer Guide (diet103/claude-code-infrastructure-showcase, 10k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars) and Claude Code Command Development (anthropics/claude-plugins-official, 38k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Creator?

ghbalf (a GitHub user) maintains it in ghbalf/freecad-ai, which has 550 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 3, 2026.

Source: ghbalf/freecad-ai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.