MCPInstall

ultrawork

Parallel execution engine for high-throughput task completion

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733
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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/yeachan-heo/oh-my-claudecode --skill ultrawork
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads ultrawork automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

<Purpose> Ultrawork is a parallel execution engine and execution protocol for independent work. It emphasizes intent grounding, parallel context gathering, dependency-aware task graphs for non-trivial work, and concise evidence-backed execution summaries. It is a component, not a standalone persistence mode -- it provides parallelism and routing guidance, but not persistence, verification loops, or long-lived state management. </Purpose>

<Use_When>

  • Multiple independent tasks can run simultaneously
  • User says "ulw", "ultrawork", or wants parallel execution
  • You need to delegate work to multiple agents at once
  • Task benefits from concurrent execution but the user will manage completion themselves </Use_When>

<Do_Not_Use_When>

  • Task requires guaranteed completion with verification -- use ralph instead (ralph includes ultrawork)
  • Task requires a full autonomous pipeline -- use autopilot instead (autopilot includes ralph which includes ultrawork)
  • There is only one sequential task with no parallelism opportunity -- delegate directly to an executor agent
  • User needs session persistence for resume -- use ralph which adds persistence on top of ultrawork </Do_Not_Use_When>

<Why_This_Exists> Sequential task execution wastes time when tasks are independent. Ultrawork enables firing multiple agents simultaneously and routing each to the right model tier, reducing total execution time while controlling token costs. It is designed as a composable component that ralph and autopilot layer on top of. </Why_This_Exists>

<Execution_Policy>

  • Fire all independent agent calls simultaneously -- never serialize independent work
  • Always pass the model parameter explicitly when delegating
  • Read docs/shared/agent-tiers.md before first delegation for agent selection guidance
  • Use run_in_background: true for operations over ~30 seconds (installs, builds, tests)
  • Run quick commands (git status, file reads, simple checks) in the foreground
  • Resolve intent and uncertainty before implementation; explore first, ask only when still blocked
  • For non-trivial tasks, produce a dependency-aware plan with parallel waves before execution
  • Keep delegated-task reports concise: short summary, files touched, verification status, blockers
  • Manual QA is required for implemented behavior, not just diagnostics </Execution_Policy>
<Steps> 1. **Read agent reference**: Load `docs/shared/agent-tiers.md` for tier selection 2. **Ground intent first**: Confirm whether the request is implementation, investigation, evaluation, or research; do not code before that is clear 3. **Gather context in parallel**: - direct tools for quick reads/searches - exploration/docs agents for broad context 4. **Classify tasks by independence**: Identify which tasks can run in parallel vs which have dependencies 5. **Create a task graph for non-trivial work**: - Parallel Execution Waves - Dependency Matrix - acceptance criteria and verification steps per task 6. **Route to correct tiers**: - Simple lookups/definitions: LOW tier (Haiku) - Standard implementation: MEDIUM tier (Sonnet) - Complex analysis/refactoring: HIGH tier (Opus) 7. **Fire independent tasks simultaneously**: Launch all parallel-safe tasks at once 8. **Run dependent tasks sequentially**: Wait for prerequisites before launching dependent work 9. **Background long operations**: Builds, installs, and test suites use `run_in_background: true` 10. **Verify when all tasks complete** (lightweight): - Build/typecheck passes - Affected tests pass - Manual QA completed for implemented behavior - No new errors introduced </Steps>

<Tool_Usage>

  • Use Task(subagent_type="oh-my-claudecode:executor", model="haiku", ...) for simple changes
  • Use Task(subagent_type="oh-my-claudecode:executor", model="sonnet", ...) for standard work
  • Use Task(subagent_type="oh-my-claudecode:executor", model="opus", ...) for complex work
  • Use run_in_background: true for package installs, builds, and test suites
  • Use foreground execution for quick status checks and file operations </Tool_Usage>
<Examples> <Good> Three independent tasks fired simultaneously: ``` Task(subagent_type="oh-my-claudecode:executor", model="haiku", prompt="Add missing type export for Config interface") Task(subagent_type="oh-my-claudecode:executor", model="sonnet", prompt="Implement the /api/users endpoint with validation") Task(subagent_type="oh-my-claudecode:executor", model="sonnet", prompt="Add integration tests for the auth middleware") ``` Why good: Independent tasks at appropriate tiers, all fired at once. </Good> <Good> Correct use of background execution: ``` Task(subagent_type="oh-my-claudecode:executor", model="sonnet", prompt="npm install && npm run build", run_in_background=true) Task(subagent_type="oh-my-claudecode:executor", model="haiku", prompt="Update the README with new API endpoints") ``` Why good: Long build runs in background while short task runs in foreground. </Good> <Bad> Sequential execution of independent work: ``` result1 = Task(executor, "Add type export") # wait... result2 = Task(executor, "Implement endpoint") # wait... result3 = Task(executor, "Add tests") # wait... ``` Why bad: These tasks are independent. Running them sequentially wastes time. </Bad> <Bad> Wrong tier selection: ``` Task(subagent_type="oh-my-claudecode:executor", model="opus", prompt="Add a missing semicolon") ``` Why bad: Opus is expensive overkill for a trivial fix. Use executor with Haiku instead. </Bad> </Examples>

<Escalation_And_Stop_Conditions>

  • When ultrawork is invoked directly (not via ralph), apply lightweight verification only -- build passes, tests pass, no new errors
  • For full persistence and comprehensive architect verification, recommend switching to ralph mode
  • If a task fails repeatedly across retries, report the issue rather than retrying indefinitely
  • Escalate to the user when tasks have unclear dependencies or conflicting requirements </Escalation_And_Stop_Conditions>

<Final_Checklist>

  • All parallel tasks completed
  • Build/typecheck passes
  • Affected tests pass
  • No new errors introduced </Final_Checklist>

Parallel session caveats

  • Multi-repo workspace anchor: drop a .omc-workspace marker at the parent directory so multiple sessions across sub-repos share one .omc/. Resolution order: OMC_STATE_DIR > .omc-workspace > git > cwd. See docs/REFERENCE.md.
  • Session id source: OMC_SESSION_ID env var wins in CLI contexts; hook payload data.session_id wins in hook contexts.
  • Plan id (when applicable): Ultrawork has no persistent state; two concurrent runs are independent by design. No plan-id needed.
  • Parallel verdict: supported (stateless component)
<Advanced> ## Relationship to Other Modes
ralph (persistence wrapper)
 \-- includes: ultrawork (this skill)
     \-- provides: parallel execution only

autopilot (autonomous execution)
 \-- includes: ralph
     \-- includes: ultrawork (this skill)

Ultrawork is the parallelism layer. Ralph adds persistence and verification. Autopilot adds the full lifecycle pipeline. </Advanced>

FAQ

What does the ultrawork skill do?

Parallel execution engine for high-throughput task completion

How do I install ultrawork?

Run npx skills add https://github.com/yeachan-heo/oh-my-claudecode --skill ultrawork in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ultrawork/ (personal) or .claude/skills/ultrawork/ (project).

Which AI agents can use ultrawork?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is ultrawork safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains ultrawork?

It is published by yeachan-heo in yeachan-heo/oh-my-claudecode. It has 733 recorded installs.

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