Parse AgentOps skills into a universal SkillBundle format, then convert to target agent platforms.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionconverterExecute the skills CLI command in your project's root directory to begin installation:
Fetches converter from boshu2/agentops and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate converter. Access via /converter in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Parse AgentOps skills into a universal SkillBundle format, then convert to target agent platforms.
/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
The converter runs a three-stage pipeline:
parse --> convert --> write
Read the source skill directory and produce a SkillBundle:
--- markers)---)references/ and scripts/references/skill-bundle-schema.md)Transform the SkillBundle into the target platform's format:
| Target | Output Format | Status |
|---|---|---|
codex |
Codex SKILL.md + prompt.md | Implemented |
cursor |
Cursor .mdc rule + optional mcp.json | Implemented |
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: reference docs, scripts, and 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, and rewrites Claude-only primitive labels to runtime-neutral wording. It preserves current flat ao CLI commands from the source skill rather than reintroducing deprecated namespace forms. 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.
Write the converted output to disk.
.agents/converter/<target>/<skill-name>/# 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]
| Argument | Required | Description |
|---|---|---|
skill-dir |
Yes (or --all) |
Path to skill directory (e.g. skills/council) |
target |
Yes | Target platform: codex, cursor, or test |
output-dir |
No | Override output location. Default: .agents/converter/<target>/<skill-name>/ |
--all |
No | Convert all skills in skills/ directory |
--codex-layout |
No | Codex-only layout mode: modular (default) or inline (legacy inlined refs/scripts) |
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 flat ao CLI preservation). 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..mdc rule file + optional mcp.json). Output: <dir>/<name>.mdc and optionally <dir>/mcp.json.To add a new target platform:
scripts/convert.sh (pattern: convert_<target>)references/ if the target format needs documentationUser says: /converter skills/council codex
What happens:
skills/council/SKILL.md frontmatter, markdown body, and any references/ and scripts/ files into a SkillBundle.SKILL.md (body + inlined references + scripts as code blocks) and a prompt.md (Codex prompt referencing the skill)..agents/converter/codex/council/.Result: A Codex-compatible skill package ready to use with OpenAI Codex CLI.
User says: /converter --all cursor
What happens:
skills/ and parses each into a SkillBundle..mdc rule file with YAML frontmatter and body content, budget-fitted to 100KB max. Skills referencing MCP servers also get a mcp.json stub..agents/converter/cursor/<skill-name>/.Result: All skills are available as Cursor rules, ready to drop into a .cursor/rules/ directory.
| Problem | Cause | Solution |
|---|---|---|
parse error: no frontmatter found |
SKILL.md is missing the --- delimited YAML frontmatter block |
Add frontmatter with at least name: and description: fields, or run /heal-skill --fix on the skill first |
Cursor .mdc output is missing references |
Total bundle size exceeded the 100KB budget limit | The converter omits references largest-first to fit the budget. Split large reference files or move non-essential content to external docs |
| Output directory already has old files | Previous conversion artifacts remain | This is expected -- the converter clean-writes by deleting the target directory before writing. If old files persist, manually delete .agents/converter/<target>/<skill>/ |
--all skips a skill directory |
The directory has no SKILL.md file |
Ensure each skill directory contains a valid SKILL.md. Run /heal-skill to detect empty directories |
Codex prompt.md description is truncated |
The skill description exceeds 1024 characters | This is by design. The converter truncates at a word boundary to fit Codex limits. Shorten the description in SKILL.md frontmatter if the truncation point is awkward |
| Conversion fails with passthrough parity check | A resource entry from source skill wasn't copied to output | Ensure source entries are readable and copyable (including nested files). Re-run conversion; failure is intentional to prevent drift between skills/ and converted output |
references/skill-bundle-schema.md -- SkillBundle interchange format specificationMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
We added converter from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend converter for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for converter matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: converter is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: converter is focused, and the summary matches what you get after install.
Keeps context tight: converter is the kind of skill you can hand to a new teammate without a long onboarding doc.
converter has been reliable in day-to-day use. Documentation quality is above average for community skills.
converter fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
converter reduced setup friction for our internal harness; good balance of opinion and flexibility.
converter has been reliable in day-to-day use. Documentation quality is above average for community skills.
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