# Skill Lifecycle Promotion

> Use when adding or auditing Agentlas skill lifecycle metadata, skill-registry.json, trial evidence, Curator promotion decisions, or first-class skill promotion gates.

- Skill: `agentlas-ai/skill-lifecycle-promotion` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentlas-ai/skill-lifecycle-promotion`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentlas-ai/skill-lifecycle-promotion/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: agentlas-ai (https://skillmd.com/u/agentlas-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/agentlas-ai/skill-lifecycle-promotion

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# Skill Lifecycle Promotion

Use this skill when a generated or packaged Agentlas repo needs governed skill
promotion metadata.

## Procedure

1. Add `.agentlas/skill-registry.json` as an export-only candidate registry.
2. Add empty `.agentlas/skill-trials.jsonl` and
   `.agentlas/curator-decisions.jsonl`.
3. Keep every skill at `tier: candidate` on export.
4. Keep `runtimeFirstClassRecallEnabled: false` unless a local Curator later
   approves promotion.
5. Add success predicates and situation tags for every skill.
6. Separate `## Memory Events` from `## Skill Trial Events`.
7. Treat LLM rubric review as weak evidence only.
8. Block promotion when authority separation, sealed holdouts, replayability, or
   rollback evidence is missing.
9. Include false-accept, blind-spot, and drift terms in any durable-error budget.

## Output

Return:

- registry files added or checked;
- promotion tier status;
- evidence gaps;
- rollback/quarantine status;
- residual risks.