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Export Skills to Agent Skills Standard

export-skills

Export SpecWeave skills to Agent Skills open standard format (agentskills.io) for cross-platform portability. Use when converting skills to GitHub Copilot, VS Code, Gemini CLI, or Cursor format. Creates portable SKILL.md files compatible with any Agent Skills-supported tool.

SKILL.md

Full skill instructions

Export Skills to Agent Skills Standard

Overview

Export SpecWeave skills to the Agent Skills open standard format. This enables skill portability across:

  • GitHub Copilot (VS Code integration)
  • Gemini CLI
  • Cursor
  • Claude Code
  • Other Agent Skills-compatible tools

Usage

/​sw:export-skills [options]

Options

OptionDescription
--output <dir>Output directory (default: .agent-skills/)
--plugin <name>Export specific plugin (default: all)
--skill <name>Export specific skill (default: all)
--dry-runPreview without writing files
--validateValidate output against Agent Skills spec

Output Structure

.agent-skills/
├── architect/
│   └── SKILL.md
├── security/
│   └── SKILL.md
├── qa-lead/
│   └── SKILL.md
└── pm/
    └── SKILL.md

Field Mapping

SpecWeave FieldAgent Skills FieldNotes
namenameDirect mapping
descriptiondescriptionDirect mapping (max 1024 chars)
allowed-toolsallowed-toolsConvert comma to space-delimited
N/​AlicenseAdd Apache-2.0 by default
N/​AcompatibilityAdd "Designed for Claude Code"
N/​Ametadata.authorUse plugin manifest author
N/​Ametadata.sourceAdd "SpecWeave"
visibility(not mapped)Agent Skills uses file placement
invocableBy(not mapped)Agent Skills discovery is implicit

Execution Steps

Step 1: Discover Skills

# Find all SKILL.md files in plugins
find plugins -name "SKILL.md" -type f

Step 2: Convert Each Skill

For each SKILL.md:

  1. Parse YAML frontmatter
  2. Extract description (truncate to 1024 chars if needed)
  3. Convert allowed-tools from comma to space-delimited
  4. Generate Agent Skills-compliant frontmatter
  5. Preserve markdown body content

Step 3: Validate Output

Each exported skill must:

  • Have name matching directory name
  • Have description between 1-1024 characters
  • Have name using only a-z and -
  • Not have -- in name
  • Not start/​end with -

Step 4: Write Files

Write to output directory with structure:

{output}/​{skill-name}/​SKILL.md

Conversion Script

interface SpecWeaveSkill {
  name: string;
  description: string;
  'allowed-tools'?: string;
  visibility?: string;
  invocableBy?: string[];
  context?: string;
  model?: string;
}

interface AgentSkill {
  name: string;
  description: string;
  license?: string;
  compatibility?: string;
  metadata?: Record<string, string>;
  'allowed-tools'?: string;
}

function convertSkill(specweave: SpecWeaveSkill, pluginName: string): AgentSkill {
  return {
    name: specweave.name,
    description: specweave.description.slice(0, 1024),
    license: 'Apache-2.0',
    compatibility: 'Designed for Claude Code (or similar products)',
    metadata: {
      author: 'specweave',
      source: 'SpecWeave',
      plugin: pluginName
    },
    'allowed-tools': specweave['allowed-tools']?.replace(/,\s*/​g, ' ')
  };
}

Example Output

Input (plugins/​specweave/​skills/​architect/​SKILL.md):

---
name: architect
description: System Architect expert...
allowed-tools: Read, Write, Edit
context: fork
model: opus
---

Output (.agent-skills/​architect/​SKILL.md):

---
name: architect
description: System Architect expert...
license: Apache-2.0
compatibility: Designed for Claude Code (or similar products)
metadata:
  author: specweave
  source: SpecWeave
  plugin: sw
allowed-tools: Read Write Edit
---

Post-Export Actions

After exporting:

  1. Commit to repo: Skills can be discovered from any subdirectory
  2. Push to GitHub: Enable Copilot skill discovery
  3. Publish: Consider publishing to skill registries

Limitations

  • SpecWeave-specific fields (context, model, invocableBy) are not exported
  • Progressive disclosure phases (sub-files) are not included
  • Skill memory files are not exported (they're runtime state)

Project-Specific Learnings

Before starting work, check for project-specific learnings:

# Check if skill memory exists for this skill
cat .specweave/​skill-memories/​export-skills.md 2>/​dev/​null || echo "No project learnings yet"

Project learnings are automatically captured by the reflection system when corrections or patterns are identified during development. These learnings help you understand project-specific conventions and past decisions.

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