ultrawork
Execute multiple independent tasks in parallel to improve workflow throughput.
Install
mkdir -p .claude/skills/ultrawork && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/840" && unzip -o skill.zip -d .claude/skills/ultrawork && rm skill.zipInstalls to .claude/skills/ultrawork
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Parallel execution engine for high-throughput task completionKey capabilities
- →Distributes tasks across multiple agents concurrently
- →Manages dependency-aware task graphs for non-trivial work
- →Routes specific tasks to optimal agent tiers
- →Reduces total execution time through parallel processing
- →Generates evidence-backed execution summaries
How it works
It fires concurrent calls to independent agents based on a task graph, routing each sub-task to the appropriate model tier to ensure efficiency.
Inputs & outputs
When to use ultrawork
- →Run multiple code analysis tasks in parallel
- →Parallelize independent data processing
- →Execute simultaneous testing routines
- →Distribute research tasks among agents
About this skill
<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
ralphinstead (ralph includes ultrawork) - Task requires a full autonomous pipeline -- use
autopilotinstead (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
ralphwhich 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
modelparameter explicitly when delegating - Read
docs/shared/agent-tiers.mdbefore first delegation for agent selection guidance - Use
run_in_background: truefor 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>
<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: truefor package installs, builds, and test suites - Use foreground execution for quick status checks and file operations </Tool_Usage>
<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
ralphmode - 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-workspacemarker at the parent directory so multiple sessions across sub-repos share one.omc/. Resolution order:OMC_STATE_DIR > .omc-workspace > git > cwd. Seedocs/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)
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>
When not to use it
- →Sequential tasks requiring strict ordering
- →Workflows needing long-lived state or session persistence
- →Single tasks without parallelism potential
Prerequisites
Limitations
- →Not designed for persistent session state management
- →Requires user-managed completion verification
- →Potential for increased token costs if improperly routed
How it compares
It actively manages agent concurrency and routing for independent tasks, rather than executing commands sequentially.
Compared to similar skills
ultrawork side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| ultrawork (this skill) | 11 | 2mo | No flags | Advanced |
| using-superpowers | 95 | 3mo | No flags | Beginner |
| clawhub | 25 | 2mo | Review | Intermediate |
| skill-installer | 29 | 1mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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