ulw-loop

SkillAI & models

Once added, your AI can take on long tasks by running them as checkpointed goal loops instead of one-off attempts. It uses ultrawork mode to decompose the work into systematic, evidence-bound steps. Each step comes with evidence that it actually worked, so progress is verifiable rather than assumed.

Available today. Use it from your connected AI after setup.

After adding the skill, give your agent a long-running task and ask it to work through it in ultrawork mode. Review the checkpoints and evidence it produces at each step.

Then ask your AI: use the ulw-loop skill

What your AI can do with it

  • Break long tasks into systematic, evidence-bound steps
  • Run tasks as checkpointed goal loops
  • Tie each step to evidence that it actually worked
  • Work in ultrawork mode

What this skill tells your AI

The instructions your AI receives, as published by code-yeongyu/oh-my-openagent in packages/omo-senpi/skills/ulw-loop/SKILL.md and read by ahel’s review.

Use this skill when the user asks for ulw-loop, ulw, durable goal execution, evidence-led work, manual QA, or checkpointed long-running delivery.

This skill is compact by design: the run contract below is the whole bootstrap. references/full-workflow.md and references/define-goal.md carry the full doctrine; open a section only when the phase you are in needs it.

Run contract

  1. Create goals: omo-agent-toolkit ulw-loop create-goals --brief "<brief>" --json. The ulw-loop skill-pointer message carries the resolved absolute CLI path for this installation; use that path verbatim. If the CLI reports the existing aggregate complete, start fresh with --session-id <new-id>.
  2. Register the aggregate objective from the printed handoff with create_goal, shaped by references/define-goal.md. Goal creation is NEVER skipped.
  3. Mirror every atomic step into the live todo checklist: one granular step per action, exactly one in_progress, transitions marked the instant they happen.
  4. Treat each goal as a phase: create its own worktree off the integration base; dispatch its dependency-ordered lanes as ONE workflow run (read the mass-ulw skill first; ordering-free lanes stay a task batch); verify every criterion with real-surface evidence; land the worktree on the integration base at checkpoint --status complete per the repository's flow (direct merge or merged PR); define the next goal's run from what this one proved. Tests alone never prove done. When a mass-ulw pointer accompanies this skill, this contract still owns goals, criteria, evidence, and checkpoints.
  5. Stop when the goal's WHEN-TO-STOP line holds with evidence in hand.

When the injected ultrawork directive accompanies this skill, its goal/notepad/todo bootstrap is subsumed by this contract: the loop CLI owns goal state and the loop ledger is the notepad — do not create a second one.

Non-Negotiables

  • Use the ulw-loop CLI state under .omo/ulw-loop; do not hand-edit goal state.
  • Register goals up front, shaped by references/define-goal.md (omo-agent-toolkit ulw-loop create-goals, then create_goal from the printed handoff), and mirror every atomic step into the live todo checklist: one ultra-granular step per action, exactly one in_progress, transitions marked the instant they happen.
  • After any compaction or context loss, re-read brief + goals + ledger FIRST plus omo-agent-toolkit ulw-loop status --json, then resume; never re-plan from scratch.
  • If omo-agent-toolkit ulw-loop create-goals says the existing aggregate is already complete, start unrelated new work with a fresh --session-id <new-id> instead of steering or forcing the completed default state. Use --force only to intentionally overwrite completed evidence.
  • Every success criterion needs observable evidence from a real surface: a channel (terminal/TUI via the xterm.js web terminal, HTTP, browser, computer-use) or, for CLI- or data-shaped criteria, an auxiliary surface (CLI stdout, DB diff, parsed config dump).
  • Evidence is bound to the tree it was captured at (git rev-parse --short "HEAD^{tree}"); it goes stale only when tracked content changes — a rebase or amend that keeps the tree identical keeps it valid. When the tree differs, re-run at the current HEAD and re-record, never relabel or regenerate. Record only after cleanup receipts exist.
  • Delegate code edits, test writes, fixes, and QA execution to right-sized omo-senpi subagents through the native task tool or through workflow nodes when the phase's lanes carry ordering.
  • Use git-master for git-tracked edits: inspect recent and touched-path commit history, then commit each verified work unit atomically in the repository's observed language, scope, and message style with only that unit's files staged. Never carry verified units into a later omnibus commit.

Team mode: decide it, do not default to it

Solo execution with parallel background task workers is the default: fan independent units out in one batched spawn, each routed to the category (or configured subagent_type) that fits it, with scopes cut so no two workers write the same files. A team (team_create) adds per-member briefing, shared-state, and relay overhead, so it must be paid for by the work's shape. Decide ONCE, when the plan's work units are known, and record the verdict plus its reason in the notepad.

Stand up a team when BOTH hold:

  1. The units' scopes overlap in a way you cannot cleanly cut. They touch the same module, contract, or migration, so one unit's discovery changes what another should do. Fire-and-forget workers cannot exchange that mid-flight; teammates can, because the lead relays it.
  2. Running them at the same time actually finishes sooner. The units are each substantial and none is merely waiting on another's output. Two units where the second only consumes the first's result are a sequence, not a team.

When the units are genuinely independent — separate files, no shared contract — spawn parallel background task workers instead and avoid the team coordination overhead entirely. When the work is one cohesive unit, do it yourself. Overlap alone is not enough: near-identical units that would collide on the same lines are faster done in sequence by one worker.

Under team mode, isolate and land per unit:

  • One git worktree per member, never a shared checkout — concurrent members editing one working tree corrupt each other's diffs and evidence. Give each member its own branch off the base and its own worktree path.
  • Merge per work unit, as each unit is verified. A member's unit lands when its own evidence is captured and its gates are green; it does not wait for the slowest sibling. Integrate each merged unit back into the base the others branch from, so overlapping members rebase onto real merged work rather than guessing at it.
  • Conflicts are the lead's job. When two members' units touch the same lines, the lead decides the order they land and tells the later member what changed; members never resolve a sibling's conflict blind.

Native Senpi Task Contract

Senpi already exposes its real subagent spawn surface through the omo-senpi task component. Use it directly. Do not route delegation through external app-server threads or another harness.

IntentNative Senpi tool
Spawn one worker`task({ prompt, subagent_type
Fan out independent workers`task({ tasks: [{ prompt, subagent_type
Send context or correctiontask_send({ task_id, message })
Inspect one midpointtask_output({ task_id, mode: "tail" })
Stop a runaway workertask_cancel({ task_id })
Coordinate overlapping workteam_create, task_create, task_get, task_list, task_update; communicate with task_send

Every worker prompt starts with TASK: and names DELIVERABLE, SCOPE, VERIFY, and STOP WHEN. Put requested skill names and all required context inside prompt; children do not inherit interview context automatically.

Signals

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skill
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ulw-loop
Source
github.com/code-yeongyu/oh-my-openagent