ultragoal

Solid

Durable 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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Quality Score: 93/100

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99
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100
Frontmatter 20%
70
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100
Issue Health 10%
50
License 10%
100
Description 5%
100

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

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