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SKILL verified MIT Self-run

Ulw Loop

skill-daeryundf2-prog-lazyantigravity-ulw-loop · by daeryundf2-prog

Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps.

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Install

$ agentstack add skill-daeryundf2-prog-lazyantigravity-ulw-loop

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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How agent discovery & health will work →
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About

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, and the Manual-QA channels table 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.
  • After any compaction or context loss, re-read brief + goals + ledger FIRST (omo sparkshell cat .omo/ulw-loop/ledger.jsonl or read directly) 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 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 (tmux, HTTP, browser, computer-use) or, for CLI- or data-shaped criteria, an auxiliary surface (CLI stdout, DB diff, parsed config dump).
  • Record evidence through the CLI only after cleanup receipts are available.
  • Delegate code edits, test writes, fixes, and QA execution to right-sized Codex subagents when the workflow requires it.
  • Every multi_agent_v1.spawn_agent message starts with TASK:, then names DELIVERABLE, SCOPE, and VERIFY; put role and specialty instructions inside message; use fork_context: false unless full history is truly required.
  • Plan and reviewer agents may run for a long time; spawn them in the background, keep doing independent root work, and poll with short multi_agent_v1.wait_agent cycles. Never use a single long blocking wait for them.
  • For work likely to exceed one wait cycle, require the child to send WORKING: - before long reading, testing, or review passes, and BLOCKED: only when it cannot progress.
  • Track spawned agent names locally. Use multi_agent_v1.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, explicitly BLOCKED:, or no longer running. Then record inconclusive and respawn a smaller fork_context: false 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.

Codex Tool Mapping

The full workflow may mention OpenCode-style orchestration examples. In Codex, translate them to native tools:

| Workflow intent | Codex tool | | --- | --- | | Plan agent | multi_agent_v1.spawn_agent({"message":"TASK: act as a planning agent. ...","fork_context":false}) | | Search/read-only worker | multi_agent_v1.spawn_agent({"message":"TASK: act as an explorer. ...","fork_context":false}) | | Implementation or QA worker | multi_agent_v1.spawn_agent({"message":"TASK: act as an implementation or QA worker. ...","fork_context":false}) | | Final verification reviewer | multi_agent_v1.spawn_agent({"message":"TASK: act as a rigorous reviewer. ...","fork_context":false}) | | Wait for background result | multi_agent_v1.wait_agent(...) | | Clean up finished worker | multi_agent_v1.close_agent(...) |

When translating load_skills=[...], include the requested skill names in the spawned agent's message.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.