ulw-loop
ulw-loop is a skill for executing complex goals through systematic, evidence-bound decomposition using ultrawork mode. Use it when managing durable goal execution, evidence-led work, manual QA cycles, or checkpointed long-running delivery that requires breaking tasks into verifiable steps, delegating to subagents, and recording observable proof from real surfaces like CLI, HTTP, or browser channels before marking work complete.
git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent /tmp/ulw-loop && cp -r /tmp/ulw-loop/packages/omo-senpi/skills/ulw-loop ~/.claude/skills/ulw-loopSKILL.md
# ulw-loop
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. Loop per goal (`status --json`, the per-criterion cycle, `checkpoint`, `complete-goals`) with real-surface evidence for every criterion. Tests alone never prove done.
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.
- Plan and reviewer agents may run for a long time; spawn them with `run_in_background: true` and keep doing independent root work.
- For work likely to exceed one wait cycle, require the child to send `WORKING: <task> - <current phase>` before long reading, testing, or review passes, and `BLOCKED: <reason>` only when it cannot progress.
- Track spawned task ids locally. Completion and progress arrive as injected notifications; use `task_output` for at most one midpoint status or transcript check per child, never a polling loop.
- While children run, surface the active subagent count, task ids, and latest `WORKING:` phase.
- If a live child needs context or correction, send it with `task_send`. Fallback only when the child completed without the deliverable, explicitly reported `BLOCKED:`, or is no longer running; then record inconclusive and spawn a smaller native `task` with the missing deliverable.
- 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 workAutomates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches.
QA the omo Codex Light edition (lazycodex / packages/omo-codex) itself, in strict isolation so ONLY our plugin is exercised, never the user's real ~/.codex. The first-party method drives the real `codex app-server` against an isolated CODEX_HOME plus a LOCAL mock model (no real API call), and proves a plugin hook fired by asserting hook/started + hook/completed notifications. Also: isolated install verification, per-component hook probes, a tmux TUI smoke, and runtime log observation (RUST_LOG / logs SQLite / /debug-config). Ships tested helper scripts each with a --self-test. Use whenever someone changes anything under packages/omo-codex or wants to QA, smoke-test, verify, or debug the Codex plugin, its hooks/components, the installer/config.toml, the app-server flow, or the Codex TUI. Triggers: codex qa, qa codex, codex-qa, test codex plugin, verify codex hook, codex app-server, lazycodex qa, isolated CODEX_HOME, prove codex hook fired, codex tui test.
MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, OMO/Senpi/pi, oh-my-pi (omp), gajae-code (gjc), OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, Aside browser-agent sessions, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/OMO/Senpi/pi/oh-my-pi/omp/gajae-code/gjc/OpenClaw/Droid/Amp/Kodu/Cursor/Aider/Aside sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this.
Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook.
Store a dag definition once and re-run it in one or two lines, instead of pasting the full definition JSON into every eval cell. MUST USE whenever the user wants to save a DAG for reuse, run a previously saved/named DAG, schedule the same graph repeatedly (nightly/weekly audits, recurring multi-agent pipelines), or asks where to put a dag definition file. Triggers: dag library, save this dag, reuse a dag, run the saved dag, stored dag definition, recurring dag, nightly dag, dag 정의 저장, 저장된 dag 실행, dag 반복 실행, DAG 만들어두고 여러 번.
Expert data processing with a hybrid engine strategy: resident-kernel engines first - DuckDB plus a resident Python stack (Polars/numpy/matplotlib) in persistent js/py eval kernels where the harness has them, bun/uv one-shots elsewhere - and per-action placement judgment (in-memory vs streaming vs remote-in-place). Triggers: 'analyze the data', 'what is in this CSV/parquet/json', 'summarize this', 'group by', 'filter rows', 'sort by', 'join these files', 'merge datasets', 'time series trend', 'compare yesterday and today', 'distribution/histogram', 'correlation', 'clean duplicates', 'handle missing values', 'dataset larger than RAM', 'SQL query on files', 'DataFrame operations', 'chart/plot this data', DuckDB vs Polars selection, quick data exploration CLI. NOT for plain text/code inspection, configs, or tiny inline math.
MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'playwright', 'flaky test', 'fails intermittently', 'passes in isolation', 'only fails in CI'.