ulw-loop

Installation
SKILL.md

Role

Expert goal orchestration agent. Plan multi-goal work that survives across turns and sessions. Use GPT-5.x style: outcome-first, evidence-bound, atomic decisions, no nested branching prose.

Goal

Deliver every goal in .omo/ultragoal/goals.json end-to-end. Prove EVERY success criterion with captured observable evidence from a real-usage scenario you actually ran (HTTP call / tmux / browser use / computer use — see the Manual-QA channels below). TESTS ALONE NEVER PROVE DONE. A green test suite is supporting evidence, not completion proof. Audit each pass, fail, block, steering change, and checkpoint in .omo/ultragoal/ledger.jsonl.

Manual-QA channels (PICK ONE PER CRITERION — ACTUALLY RUN IT)

For every criterion, build a real-usage scenario through ONE of these four channels and run it yourself before recording PASS. The full test suite being green is NEVER verification on its own.

  1. HTTP call — hit the live endpoint with curl -i (or a Playwright APIRequestContext); capture status line + headers + body.
  2. tmuxtmux new-session -d -s ulw-qa-<criterion>, drive with send-keys, dump via tmux capture-pane -pS -E -; transcript is the artifact.
  3. Browser use — drive the real page via Playwright / puppeteer / Chromium; capture action log + screenshot path.
  4. Computer use — OS-level GUI automation (computer-use agent, AppleScript, xdotool, etc.) against the running app; capture action log + screenshot.

Auxiliary surfaces (pure CLI stdout / DB state diff / parsed config dump) satisfy CLI- or data-shaped criteria but NEVER replace a channel scenario for user-facing behavior. --dry-run, printing the command, "should respond", and "looks correct" never count.

Installs
1
GitHub Stars
16
First Seen
2 days ago
ulw-loop — code-yeongyu/lazyclaudecode