/package

Package Skill for Distribution

Package an existing skill for distribution on Claude.ai, Claude Code, or both.

Input

The user provides: $ARGUMENTS

If $ARGUMENTS is a path, use it directly. If $ARGUMENTS is empty, ask: "Which skill should I package? Provide the path to the skill folder."

Step 1: Pre-Package Validation

Run quick validation first (same as /skill-maker:validate). If critical issues found, warn the user and offer to fix before packaging.

Step 2: Choose Target

Ask the user:

Package target:
1. Claude.ai (zip file for upload)
2. Claude Code plugin (plugin scaffold)
3. Both

Step 3: Project Scan & Output Location

Before packaging, scan the project to suggest the best output location.

3a: Project Discovery

Scan the working directory and surrounding project structure:

• Read package.json, pyproject.toml, composer.json, or similar manifest (if present)
• Glob for existing skill-related directories: **/skills/, **/*-plugin/, **/.claude-plugin/
• Glob for existing zip packages: **/*.zip matching skill patterns
• Check for common project structures: src/, dist/, build/, output/, packages/
• Note the current working directory and the skill source location

3b: Suggest Output Location

Present a summary of what was found and suggest locations:

PROJECT SCAN: [project name or cwd]
═══════════════════════════════════

[If relevant structures found:]
Detected:
  - Skills directory: ./skills/ (contains X skills)
  - Plugin directory: ./plugins/ (contains Y plugins)
  - Existing packages: ./dist/skill-name.zip

[If nothing specific found:]
No existing skill/plugin directories detected.

Then ask where to save the packaged output. Build the options dynamically based on what was found:

For Claude.ai (zip):

Where should I save the zip package?
1. [Detected path, e.g., ./dist/skill-name.zip] (Recommended — existing packages here)
2. Same directory as source skill: [source-parent]/[skill-name].zip
3. Current directory: ./[skill-name].zip
4. Custom path

For Claude Code (plugin scaffold):

Where should I create the plugin scaffold?
1. [Detected path, e.g., ./plugins/skill-name-plugin/] (Recommended — existing plugins here)
2. Next to source skill: [source-parent]/[skill-name]-plugin/
3. Current directory: ./[skill-name]-plugin/
4. Custom path

Rules for suggestions:

• If a plugins/ directory exists with other .claude-plugin/ manifests, suggest it first as recommended
• If a skills/ directory exists, suggest the parent of that directory
• If existing .zip skill packages are found, suggest the same directory
• If nothing is detected, suggest current directory as recommended
• Always include the custom path option
• For "Both" target, ask once with combined options or ask separately per target

Option 1: Claude.ai Package

1. Verify the skill folder structure is correct
2. Create a zip file containing the skill folder:

   skill-name/
   ├── SKILL.md
   ├── references/
   ├── scripts/
   └── assets/
   

3. Save the zip to the location chosen in Step 3
4. Provide upload instructions:

   Upload to Claude.ai:
   1. Go to Settings > Capabilities > Skills
   2. Click "Upload skill"
   3. Select [skill-name].zip
   4. Toggle the skill ON
   5. Test: Ask Claude "[trigger phrase]"
   

Option 2: Claude Code Plugin

1. Create a plugin scaffold at the location chosen in Step 3:

   skill-name-plugin/
   ├── .claude-plugin/
   │   └── plugin.json
   ├── skills/
   │   └── skill-name/
   │       ├── SKILL.md
   │       ├── references/
   │       ├── scripts/
   │       └── assets/
   └── README.md
   

2. Generate plugin.json:

   {
     "name": "[skill-name]",
     "version": "1.0.0",
     "description": "[from SKILL.md description]",
     "author": { "name": "[ask user]" },
     "keywords": ["[from metadata tags]"],
     "license": "[from SKILL.md or MIT]"
   }
   

3. Generate README.md with:

   • Plugin description
   • Installation instructions
   • Usage examples
   • Trigger phrases

4. Provide installation instructions:

   Install in Claude Code:
   claude --plugin-dir /path/to/skill-name-plugin
   

Option 3: Both

Run both packaging processes. Save outputs to the locations chosen in Step 3.

Pre-Distribution Checklist

Before packaging, verify:

• Skill passes /skill-maker:validate with no critical issues
• /skill-maker:test trigger tests show 90%+ accuracy
• At least one functional test passes
• Description focuses on OUTCOMES, not implementation details
• Version number set in metadata (if applicable)

Positioning Guidance

When writing the README or marketplace description, focus on outcomes:

Good: "Set up complete project workspaces in seconds - including pages, databases, and templates - instead of spending 30 minutes on manual setup."

Bad: "A folder containing YAML frontmatter and Markdown instructions that calls MCP server tools."

If the skill enhances an MCP server, highlight both: "Our MCP server gives Claude access to your [Service]. This skill teaches Claude your team's [workflow]. Together, they enable [outcome]."

Post-Package

Present summary:

PACKAGED: [skill-name]
═══════════════════════

Claude.ai:   [chosen-path]/[skill-name].zip (X KB)
Claude Code:  [chosen-path]/[skill-name]-plugin/ (Y files)

Next steps:
- Test locally before distributing
- Run /skill-maker:test to verify trigger accuracy
- Consider hosting on GitHub for sharing
- Add to a marketplace if available

Distribution tips:
- Write README focusing on outcomes, not features
- Include example usage and screenshots
- Provide a quick-start guide (3 steps max)
- For MCP skills: document required environment and auth setup