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Misc70k · #1746

ulw-execute

Executes detailed work plans, managing tasks and progress. It's useful for following a complex plan step by step.

What it does

This agent executes detailed work plans. It coordinates other AI tools to get tasks done, without doing the work itself.

When to use it

  • ✓When you have a work plan (.omo/plans) to execute.
  • ✓When you want the AI to manage the execution of complex tasks.
  • ✓When you need the AI to delegate work to other AIs.

Example of what to ask your AI

“Execute the 'improve_documentation' plan with the option to create a pull request.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/code-yeongyu/oh-my-openagent/blob/dev/packages/shared-skills/skills/ulw-execute/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/code-yeongyu/oh-my-openagent/blob/dev/packages/shared-skills/skills/ulw-execute/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It selects the correct plan, manages the work state, and delegates each step to other specialized AIs. It tracks progress and ensures everything is completed.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add code-yeongyu/oh-my-openagent --skill ulw-execute

Or download just the file:

curl -L https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/dev/packages/shared-skills/skills/ulw-execute/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

ABSOLUTE RULE: YOU ARE AN ORCHESTRATOR — NEVER THE IMPLEMENTER

YOU DO NOT WRITE CODE. YOU DO NOT EDIT PRODUCT FILES. YOU DO NOT RUN QA YOURSELF. EVERY unit of implementation, test, QA, and review work MUST be delegated to a spawned subagent. NO EXCEPTIONS. Your hands touch only plan selection, .omo/ state (Boulder, ledger, plan checkboxes), decomposition, dispatch, verdicts, and evidence records. About to edit a product file or run an implementation command yourself? STOP. SPAWN A WORKER INSTEAD. Orchestrate at MAXIMUM PARALLELISM: every independent unit runs concurrently; only named dependencies serialize.

Codex Harness Tool Compatibility

Translate any OpenCode-only tool name in an inherited example to its Codex equivalent:

OpenCode example Codex tool to use
final-review task(...) multi_agent_v1.spawn_agent({"message":"TASK: act as a rigorous reviewer. ...","agent_type":"lazycodex-gate-reviewer","fork_context":false})
worker task(...) multi_agent_v1.spawn_agent({"message":"TASK: act as <role>. ...","fork_context":false}) — for implementation workers add `agent_type: "lazycodex-worker-<low
background_output(task_id="...") multi_agent_v1.wait_agent(...) for mailbox signals
team_*(...) multi_agent_v1.spawn_agent + multi_agent_v1.send_input + multi_agent_v1.wait_agent + multi_agent_v1.close_agent

When translating load_skills=[...], name the skills inside the spawned agent's message. If a code block below conflicts with this section, this section wins.

Codex exposes ONE of two subagent tool surfaces per session; check your own tool list and route accordingly. If multi_agent_v1.* tools exist, use the table above as written. If instead a flat spawn_agent with a required task_name exists (multi_agent_v2), rewrite every multi_agent_v1.* example: multi_agent_v1.spawn_agent({...,"fork_context":false}) becomes spawn_agent({"task_name":"<lowercase_digits_underscores>","message":...,"agent_type":...,"fork_turns":"none"}) ("all" only when full parent history is truly required); send_input becomes send_message; do not call close_agent/resume_agent (finished agents end on their own; followup_task re-tasks one, interrupt_agent stops one); wait_agent takes only timeout_ms and returns on any child mailbox activity. On the v2 surface agent_type may be absent from the spawn schema — when absent, omit it and describe the role inside message. If a code block below conflicts with this section, this section wins.

Codex tier mapping for the delegation router

When tier worker agents are installed, map the delegation router's parenthesized difficulty to agent_type: (low) -> lazycodex-worker-low; (medium) -> lazycodex-worker-medium; (high) -> lazycodex-worker-high. Explorer/librarian research lanes keep their own roles. On spawn surfaces without agent_type, state the tier inside message. Difficulty (model power) is orthogonal to the LIGHT/HEAVY rigor tier in step 4 — judge each on its own facts.

Codex Subagent Reliability

Every multi_agent_v1.spawn_agent message is a self-contained executable assignment: TASK: <imperative assignment>, then DELIVERABLE, SCOPE, and VERIFY, with role instructions inside message. Use fork_context: false unless full history is truly required; paste only the context the child needs.

Plan and reviewer agents may run for a long time: spawn them in the background and keep doing independent root work. Between multi_agent_v1.wait_agent calls, back off — double the timeout up to ~5 minutes — instead of spinning short cycles. A timeout only means no new mailbox update arrived; treat a running child as alive. Require WORKING: <task> - <current phase> before long passes and BLOCKED: <reason> only when progress stops. Keep the parent visibly alive with active subagent count, names, and latest WORKING: phase. Fallback only when the child is completed without the deliverable, ack-only after followup, explicitly BLOCKED:, or no longer running — then record inconclusive (never a pass), close if safe, and respawn a smaller fork_context: false task with the missing deliverable.

ulw-execute

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FAQ

What does 'Orchestrator' mean?

It means it manages and coordinates other AIs, but doesn't perform the coding or review tasks directly.

What is a '.omo/plans'?

It's a file containing a detailed work plan, like a to-do list for tasks to be executed.

What are 'subagents'?

These are other AI tools that the main 'ulw-execute' agent delegates specific tasks to be performed.

Details

Original description by the author

Executes a written ulw-plan work plan with Boulder state, evidence ledger, worktree discipline, and parallel subagents. Use when the user says ulw-execute or asks to run a .omo/plans plan.

repo: code-yeongyu/oh-my-openagent

Popularity

GitHub stars
70k
Ranking position
#1746
License
NOASSERTION
Updated
10/16/2026

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