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Agents48k · #4182

skill-porter

Lets your agent translate tool names and copy skill packages. It helps adapt tools for different systems.

What it does

This tool helps prepare skills (sets of instructions) for a new system called Google Antigravity. It checks and copies necessary files, making small adjustments to tool names.

When to use it

  • ✓When adapting a local skill for Google Antigravity.
  • ✓To preview how tool names will be translated.
  • ✓When copying a complete skill file bundle.

Example of what to ask your AI

“How do I prepare my local skill 'my-agent' for Google Antigravity?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/skill-porter/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/skill-porter/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

You point the tool to your skill's folder. It shows you the changes it will make and then copies the files to a new location, ready for use.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill skill-porter

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/skill-porter/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Skill Porter for Google Antigravity

When to Use

Use when adapting a locally obtained Claude Code, Cursor, Codex, or generic agent skill bundle for Google Antigravity. The utility preserves support files and previews limited tool-name substitutions; it does not prove client compatibility.

Prerequisites

  • Python 3.9+; standard library only.
  • A reviewed local skill directory containing SKILL.md, that file itself, or a repository with skills/<lowercase-hyphenated-id>/SKILL.md directories.
  • Verify the upstream identity, pinned revision, license and complete bundle first. Obtain remote material separately through your reviewed download/clone workflow.
  • Use stable local directories you control. Do not run against a tree being modified by another process or user. Inspect scripts without executing them.

Workflow

  1. From this skill directory, preview the local bundle:

    python3 scripts/port_skill.py --source "/absolute/path/my-skill" --dry-run
    
  2. Review the diff. Only exact backtick-quoted tool identifiers such as View, Edit, and Bash change. Frontmatter and support bytes remain intact. Verify each target tool and its argument semantics in your actual client.

  3. Copy to a fresh staging destination, then inspect before activating:

    python3 scripts/port_skill.py --source "/absolute/path/my-skill" --dest "/absolute/path/staging"
    

    Existing skill destinations are rejected; no global paths are written.

  4. When the user requests workspace installation, verify the current project:

    python3 scripts/port_skill.py --source "/absolute/path/my-skill" --workspace --dry-run
    python3 scripts/port_skill.py --source "/absolute/path/my-skill" --workspace
    

    This writes only .agents/skills/<id> under the current working directory. Confirm that discovery path is supported by the intended host first.

  5. Review context-file references, tool argument shapes, client configuration, dependencies, licensing and multi-agent ordering manually. Validate the adapted skill and test actual client invocation before claiming compatibility.

Examples

For a multi-skill repository, use its local root as the source:

python3 scripts/port_skill.py --source "/absolute/path/reviewed-repository" --dry-run
python3 scripts/port_skill.py --source "/absolute/path/reviewed-repository" --dest "/absolute/path/fresh-output"

A source-only invocation defaults to preview. Remote URLs are rejected; obtain and inspect a pinned local checkout first. Run bundled tests from this directory:

PYTHONDONTWRITEBYTECODE=1 python3 -m unittest scripts/test_port_skill.py -v

Limitations

  • Conservative text adaptation only: no AST conversion, semantic optimization, automatic parallelization, artifact generation, or compatibility certification.
  • Context references and support scripts retain their original bytes and may need manual adaptation. Binary support files are copied intact, never interpreted.
  • Symbolic links and non-regular files are rejected. Input is bounded to 1,000 files and 20 MiB. This is not a sandbox against concurrent hostile filesystem changes; use only stable directories you control.
  • Disk or filesystem failure may leave a partial new destination. Inspect it and choose a fresh output for retries. There is no overwrite or rollback mode.
  • No downloads, credentials, network calls, global installation, plugin manifest generation/registration or external MCP setup. Verify tool availability in the actual host, whose version and capabilities may differ.

Source and license

Adapted from Pranav-Nexus/antigravity-skill-porter. The upstream MIT notice is preserved in LICENSE.

FAQ

What are 'skills'?

They are sets of instructions you give to an AI to follow, like a small program or script.

What is 'Google Antigravity'?

It's the name of a new system or platform you are adapting your AI skills for.

Does the tool check if the skill will work perfectly?

No, it only prepares the files and shows the changes. You still need to test the skill in the new system.

Details

Original description by the author

Preview conservative tool-name translations and copy complete local skill bundles for manual adaptation to Google Antigravity.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4182
License
MIT
Updated
10/15/2026

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