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/skill-forge-convert

Convert Claude Code skills to work on OpenAI Codex, Google Gemini CLI, Google Antigravity, and Cursor. Analyzes platform-specific features, generates target files (openai.yaml, AGENTS.md, GEMINI.md, .mdc rules), adapts frontmatter, converts MCP config, and produces compatibility

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From plugin
skill-forge
1858 skills8 agents
Install
$ npx -y skills add AgriciDaniel/skill-forge --skill skill-forge-convert --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/skill-forge-convert

Context preview

The summary Claude sees to decide when to auto-load this skill.

Convert Claude Code skills to work on OpenAI Codex, Google Gemini CLI, Google Antigravity, and Cursor. Analyzes platform-specific features, generates target files (openai.yaml, AGENTS.md, GEMINI.md, .mdc rules), adapts frontmatter, converts MCP config, and produces compatibility

SKILL.md

skill-forge-convert.SKILL.md
name: skill-forge-convert
description: >
  Convert Claude Code skills to work on OpenAI Codex, Google Gemini CLI, Google
  Antigravity, and Cursor. Analyzes platform-specific features, generates target
  files (openai.yaml, AGENTS.md, GEMINI.md, .mdc rules), adapts frontmatter,
  converts MCP config, and produces compatibility reports. Use when user says
  "convert skill", "port skill", "multi-platform", "skill for codex",
  "skill for gemini", "skill for antigravity", "skill for cursor",
  "cross-platform skill", "convert to codex", "convert to gemini",
  "convert to antigravity", or "convert to cursor".

Skill Conversion — Multi-Platform

Convert Claude Code skills to work on OpenAI Codex, Google Gemini CLI, Google Antigravity, and Cursor while maintaining quality and following each platform's best practices.

Process

Step 1: Read Source Skill

1. Read the source `SKILL.md` and parse frontmatter 2. Detect skill complexity tier (1-4) 3. Inventory all files: scripts/, references/, agents/, sub-skills 4. Identify MCP config (`.mcp.json`) if present

Step 2: Analyze Platform Compatibility

Run dry-run analysis first:

python scripts/convert_skill.py <path> --dry-run --target all

Review the compatibility report:

  • **Portable fields**: Transfer directly (name, description, license)
  • **Adaptable fields**: Need platform-specific handling
  • **Claude-only fields**: Will be stripped with warnings

Step 3: Convert to Target Platforms

Run the conversion:

python scripts/convert_skill.py <path> --target codex,gemini,antigravity,cursor --output dist/

For MCP config conversion:

python scripts/convert_skill.py <path> --target all --output dist/ --include-mcp

Step 4: Handle Claude-Only Features

Features that need manual adaptation per platform:

| Claude Feature | Codex | Gemini/Antigravity | Cursor | |---------------|-------|-------------------|--------| | `allowed-tools` | Supported | Remove; all tools available | Remove; no equivalent | | `context: fork` | No equivalent | No equivalent | No equivalent | | `hooks` | 1 event (notify) | Partial (CLI) | 6 events (beta) | | `model` selection | No equivalent | No equivalent | No equivalent | | `Task` delegation | Break into separate skills | Break into separate skills | Background Agents (Ultra plan) | | `/slash` commands | `$mention` syntax | Description-based activation | Description-based + `@rule` | | Sub-skill routing | Separate skills with `$mention` | Separate skills, LLM-routed | Separate skills, LLM-routed |

Step 5: Validate Converted Skills

Run validation on each generated output:

python scripts/validate_skill.py dist/codex/<skill-name>/
python scripts/validate_skill.py dist/gemini/<skill-name>/
python scripts/validate_skill.py dist/antigravity/<skill-name>/
python scripts/validate_skill.py dist/cursor/<skill-name>/

Fix any critical or high-priority issues before proceeding.

Step 6: Generate Deployment Report

Present the user with a summary:

## Conversion Report: {skill-name}

| Platform | Score | Files | Warnings | Manual Steps |
|----------|-------|-------|----------|-------------|
| Codex | 92% | 4 | 2 | 1 |
| Gemini | 88% | 3 | 3 | 1 |
| Antigravity | 88% | 3 | 3 | 1 |
| Cursor | 88% | 3 | 3 | 1 |

### Generated Files
[list per platform]

### Warnings
[list per platform]

### Manual Steps Required
[list per platform]

Step 7: Generate Multi-Platform Install Script

When converting for all platforms (`--target all`), the script auto-generates `install-multiplatform.sh` that:

  • Auto-detects the current agent platform
  • Installs to the correct skill path
  • Supports `--platform` flag for explicit selection

Platform Quick Reference

| Platform | Skill Path | Instruction File | Config Format | |----------|-----------|-----------------|---------------| | Claude Code | `.claude/skills/` | `CLAUDE.md` | JSON (`.mcp.json`) | | OpenAI Codex | `.agents/skills/` | `AGENTS.md` | TOML (`config.toml`) | | Gemini CLI | `.gemini/skills/` | `GEMINI.md` | JSON (`settings.json`) | | Antigravity | `.agent/skills/` | `GEMINI.md` | JSON (`mcp_config.json`) | | Cursor | `.cursor/skills/` | `.cursor/rules/*.mdc` | JSON (`mcp.json`) |

For full platform specs, load `references/platforms.md`.

Tier Conversion Guidelines

  • **Tier 1** (single SKILL.md): Converts cleanly. Auto-convert recommended.
  • **Tier 2** (skill + scripts): Converts well. Verify script paths.
  • **Tier 3** (multi-skill): Partial. Each sub-skill converts independently. Routing needs manual work.
  • **Tier 4** (ecosystem): Manual review required. Subagent delegation needs platform adaptation.
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