ulw-loop

A workflow for breaking large goals into smaller, checkable steps and continuing work through recorded checkpoints. It is intended for long-running coding tasks that need evidence and manual quality checks.

In plain words
What is it for?
Use it for durable multi-step implementation, testing, quality assurance, and delivery work that needs checkpoints and explicit stop conditions.
Why use it?
It makes progress visible and reduces the chance that tests or partial work are mistaken for a finished result.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/code-yeongyu/lazycodex/ulw-loop
Any agent
npx skills add code-yeongyu/lazycodex --skill ulw-loop
Clone the repo
git clone --depth 1 https://github.com/code-yeongyu/lazycodex

Made for: Claude Code, Codex.

Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,726 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.01726
Opus 5 $0.00012 $0.00863
Sonnet 5 $0.00005 $0.00345
Haiku 4.5 $0.00002 $0.00173

Measured 2d ago against content hash 615f11ab07bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ulw-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/omo/components/ulw-loop/skills/ulw-loop/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 intentionally compact. The full workflow lives in references/full-workflow.md. Read only the sections needed for the current phase, then execute them exactly.

Required First Steps

  1. Open references/full-workflow.md.
  2. Read through Bootstrap (including its tier triage), Execution Loop, the Manual-QA channels table, and the Stop Rules before running any ULW command or recording evidence.
  3. If the task has code edits, tests, QA, or commit work, follow the full workflow's delegation and evidence rules. Tests alone never prove done.

Non-Negotiables

  • Use the ulw-loop CLI state under .omo/ulw-loop; do not hand-edit goal state.
  • Register goals up front (omo ulw-loop create-goals, then create_goal from the printed handoff) and mirror every atomic step into the live update_plan 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 ulw-loop status --json, then resume; never re-plan from scratch.
  • If omo 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 Codex subagents when the workflow requires it.
  • Every spawn_agent message starts with TASK:, then names DELIVERABLE, SCOPE, and VERIFY; put role and specialty instructions inside message; use fork_turns: "none" (v1: fork_context: false) unless full history is truly required.
  • Plan and reviewer agents may run for a long time; spawn them in the background and keep doing independent root work. Between wait_agent calls, back off — double the timeout up to ~5 minutes — instead of spinning short cycles.
  • 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 agent names locally. Use wait_agent for mailbox signals, not proof of completion. A timeout only means no new mailbox update arrived. Treat a running child as alive.
  • While children run, surface the active subagent count, agent names, and latest WORKING: phase.
  • Fallback only when the child is completed without the deliverable, ack-only after followup_task, explicitly BLOCKED:, or no longer running. Then record inconclusive and respawn a smaller fork_turns: "none" 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.

Read the full file on GitHub · 69 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 69 lines · 24 tokens per session scan A 615f11ab07bf

Subscribe to this mod's changes

ulw-loop is a skill published in the GitHub repository code-yeongyu/lazycodex (3,350 stars, last pushed 23d ago), licensed MIT. It adds 24 tokens to every session and 1,726 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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