/converter — Cross-Platform Skill Converter

Parse AgentOps skills into a universal SkillBundle format, then convert to target agent platforms.

Quick Start

/converter skills/council codex     # Convert council skill to Codex format
/converter skills/vibe cursor       # Convert vibe skill to Cursor format
/converter --all codex              # Convert all skills to Codex

Pipeline

The converter runs a three-stage pipeline:

parse --> convert --> write

Stage 1: Parse

Read the source skill directory and produce a SkillBundle:

• Extract YAML frontmatter from SKILL.md (between --- markers)
• Collect the markdown body (everything after the closing ---)
• Enumerate all files in references/ and scripts/
• Assemble into a SkillBundle (see references/skill-bundle-schema.md)

Stage 2: Convert

Transform the SkillBundle into the target platform’s format:

The Codex adapter produces a SKILL.md with YAML frontmatter (name, description) plus rewritten body content and a prompt.md (Codex prompt referencing the skill). Default mode is modular: references/scripts/resources are copied as files and SKILL.md includes a local resource index instead of inlining everything. Optional inline mode preserves the older behavior by appending inlined references and script code blocks. Codex output rewrites known slash-skill references (for example /plan) to dollar-skill syntax ($plan), replaces Claude-specific paths/labels (including ~/.claude/, $HOME/.claude/, and /.claude/ path variants), normalizes common mixed-runtime terms (for example Claude Native Teams, claude-native-teams, and Claude session/runtime) to Codex-native phrasing, rewrites Claude-only primitive labels to runtime-neutral wording, and rewrites flat ao command references to namespace-qualified forms expected by Codex-native lint. It also deduplicates repeated “In Codex” runtime headings after rewrite while preserving section content. It preserves non-generated resource files/directories from the source skill (for example templates/, assets/, schemas/, examples/, agents/) and enforces passthrough parity (missing copied resources fail conversion). Descriptions are truncated to 1024 chars at a word boundary if needed.

The Cursor adapter produces a <name>.mdc rule file with YAML frontmatter (description, globs, alwaysApply: false) and body content. References are inlined into the body, scripts are included as code blocks. Output is budget-fitted to 100KB max — references are omitted largest-first if the total exceeds the limit. If the skill references MCP servers, a mcp.json stub is also generated.

Stage 3: Write

Write the converted output to disk.

• Default output directory: .agents/converter/<target>/<skill-name>/
• Write semantics: Clean-write. The target directory is deleted before writing. No merge with existing content.

CLI Usage

# Convert a single skill
bash skills/converter/scripts/convert.sh <skill-dir> <target> [output-dir]
bash skills/converter/scripts/convert.sh --codex-layout inline <skill-dir> codex [output-dir]

# Convert all skills
bash skills/converter/scripts/convert.sh --all <target> [output-dir]

Arguments

Supported Targets

• codex — Convert to OpenAI Codex format (SKILL.md + prompt.md) with codex-native rewrites (slash-to-dollar skills, .claude path variants to .codex, mixed-runtime term normalization to Codex phrasing, Claude primitive label neutralization, duplicate runtime-heading cleanup, and namespace-qualified ao command references). Default is modular output with copied resources and a SKILL.md local-resource index; pass --codex-layout inline for legacy inlined refs/scripts. Converter enforces passthrough parity so missing copied resources fail fast. Output: <dir>/SKILL.md, <dir>/prompt.md, and copied resources.
• cursor — Convert to Cursor rules format (.mdc rule file + optional mcp.json). Output: <dir>/<name>.mdc and optionally <dir>/mcp.json.
• test — Emit the raw SkillBundle as structured markdown. Useful for debugging the parse stage.

Extending

To add a new target platform:

1. Add a conversion function to scripts/convert.sh (pattern: convert_<target>)
2. Update the target table above
3. Add reference docs to references/ if the target format needs documentation

Examples

Converting a single skill to Codex format

User says: /converter skills/council codex

What happens:

1. The converter parses skills/council/SKILL.md frontmatter, markdown body, and any references/ and scripts/ files into a SkillBundle.
2. The Codex adapter transforms the bundle into a SKILL.md (body + inlined references + scripts as code blocks) and a prompt.md (Codex prompt referencing the skill).
3. Output is written to .agents/converter/codex/council/.

Result: A Codex-compatible skill package ready to use with OpenAI Codex CLI.

Batch-converting all skills to Cursor rules

User says: /converter --all cursor

What happens:

1. The converter scans every directory under skills/ and parses each into a SkillBundle.
2. The Cursor adapter transforms each bundle into a .mdc rule file with YAML frontmatter and body content, budget-fitted to 100KB max. Skills referencing MCP servers also get a mcp.json stub.
3. Each skill’s output is written to .agents/converter/cursor/<skill-name>/.

Result: All skills are available as Cursor rules, ready to drop into a .cursor/rules/ directory.

Troubleshooting

References

• references/skill-bundle-schema.md — SkillBundle interchange format specification

Reference Documents

• references/skill-bundle-schema.md