{
  "slug": "ai-done",
  "title": "AI Done",
  "description": "The done bar for probabilistic AI / LLM / agent features: eval bands, failure triage, tripwires, rehearsed rollback, post-ship loop. Use when: \"is this AI feature done\", \"ready to ship the model/agent\", \"calibrate this AI feature\", \"AI done bar\", \"how do I know this model/agent is ready\", \"done bar for a probabilistic feature\", \"ship checklist for an LLM feature\". Non-AI deterministic features use /success-criteria; this runs after its checklist.",
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  "tags": {
    "tool": [
      "Claude Code",
      "Codex"
    ],
    "task": [
      "Workflow"
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  "author": "Joy Dong",
  "license": "MIT",
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  "source": "https://github.com/joydai2026-del/skills/tree/0d15d89c093f8f3852fe51befb3c364e387244f1/ai-done",
  "page": "https://www.joydong.org/skills/ai-done",
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  "teaching_published": false,
  "verified": {
    "status": "pass_install",
    "recorded_status": "pass",
    "last_run_at": "2026-09-11T01:24:01Z",
    "runner": "github-actions",
    "runner_digest": "sha256:b573c7946174ef251554e541b13e12f280b1c9977e3f17607042aa6715e90d36",
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      "skills_cli": "1.5.25"
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  "last_updated": "2026-09-10T18:56:00Z"
}