32 specialized agents with smart model routing, persistent execution loops, and real-time visibility for Claude Code workflows.
Works with
Six orchestration modes (Team, Autopilot, Ralph, Ultrawork, Pipeline, Swarm) handle everything from coordinated multi-stage pipelines to autonomous single-agent execution and maximum parallelism
Team mode runs a canonical five-stage pipeline: plan → PRD → execute → verify → fix, with automatic looping until tasks complete
Magic keywords (autopilot, ralph, ul
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionomcExecute the skills CLI command in your project's root directory to begin installation:
Fetches omc from supercent-io/skills-template 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 omc. Access via /omc 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
5
total installs
5
this week
88
GitHub stars
0
upvotes
Run in your terminal
5
installs
5
this week
88
stars
Step 1: Install plugin
/plugin marketplace add https://github.com/Yeachan-Heo/oh-my-claudecode
/plugin install oh-my-claudecode
Step 2: Run setup
/omc:omc-setup
Step 3: Build something
autopilot: build a REST API for managing tasks
npm alternative:
npm install -g oh-my-claude-sisyphus
| Mode | What it is | Use For |
|---|---|---|
| Team (recommended) | Staged pipeline: team-plan → team-prd → team-exec → team-verify → team-fix |
Coordinated agents on shared task list |
| Autopilot | Autonomous single lead agent | End-to-end feature work with minimal ceremony |
| Ultrawork | Maximum parallelism (non-team) | Burst parallel fixes/refactors |
| Ralph | Persistent mode with verify/fix loops | Tasks that must complete fully |
| Pipeline | Sequential staged processing | Multi-step transformations |
| Swarm/Ultrapilot | Legacy facades → route to Team | Existing workflows |
Enable Claude Code native teams in ~/.claude/settings.json:
{
"env": {
"CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"
}
}
| Keyword | Effect | Example |
|---|---|---|
team |
Canonical Team orchestration | /omc:team 3:executor "fix all TypeScript errors" |
autopilot |
Full autonomous execution | autopilot: build a todo app |
ralph |
Persistence mode | ralph: refactor auth |
ulw |
Maximum parallelism | ulw fix all errors |
plan |
Planning interview | plan the API |
ralplan |
Iterative planning consensus | ralplan this feature |
swarm |
Legacy (routes to Team) | swarm 5 agents: fix lint errors |
ultrapilot |
Legacy (routes to Team) | ultrapilot: build a fullstack app |
Note:
ralphincludes ultrawork — activating ralph mode automatically includes ultrawork's parallel execution.
/omc:team 3:executor "fix all TypeScript errors"
Runs as a staged pipeline:
team-plan → team-prd → team-exec → team-verify → team-fix (loop)
Auto-resume Claude Code sessions when rate limits reset:
omc wait # Check status, get guidance
omc wait --start # Enable auto-resume daemon
omc wait --stop # Disable daemon
omc config-stop-callback telegram --enable --token <bot_token> --chat <chat_id>
omc config-stop-callback discord --enable --webhook <url>
# 1. Sync latest version
/plugin marketplace update omc
# 2. Re-run setup
/omc:omc-setup
# If issues after update
/omc:omc-doctor
OMC can optionally orchestrate external AI providers (not required):
| Provider | Install | What it enables |
|---|---|---|
| Gemini CLI | npm install -g @google/gemini-cli |
Design review, UI consistency (1M token context) |
| Codex CLI | npm install -g @openai/codex |
Architecture validation, code review cross-check |
| Action | Command |
|---|---|
| Install | /plugin marketplace add https://github.com/Yeachan-Heo/oh-my-claudecode |
| Setup | /omc:omc-setup |
| Team mode | /omc:team N:executor "task" |
| Autopilot | autopilot: <task> |
| Ralph loop | ralph: <task> |
| Ultrawork | ulw <task> |
| Update | /plugin marketplace update omc && /omc:omc-setup |
| Debug | /omc:omc-doctor |
Make 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.
supercent-io/skills-template
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Keeps context tight: omc is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added omc from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend omc for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
omc reduced setup friction for our internal harness; good balance of opinion and flexibility.
omc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for omc matched our evaluation — installs cleanly and behaves as described in the markdown.
omc has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in omc — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
omc fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: omc is focused, and the summary matches what you get after install.
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