ultragoal
SolidDurable repo-native multi-goal plans with embedded success criteria and evidence audit.
AI & Automation 941 stars
47 forks Updated today MIT
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Skill Content
## 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. **tmux** — `tmux 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...
Details
- Author
- code-yeongyu
- Repository
- code-yeongyu/lazycodex
- Created
- 2 weeks ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
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