# Dataset Retire

> Plan and delegate safe dataset retirement, tombstoning, derived-artifact cleanup, and reconciliation.

- Skill: `jmagly/dataset-retire` (Agent Skill)
- Install (CLI): `npx skillmds@latest add jmagly/dataset-retire`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jmagly/dataset-retire/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: jmagly (https://skillmd.com/u/jmagly)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jmagly/dataset-retire

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# Dataset Retirement

First encode the retirement operation and complete enumeration in a governed
plan input, then use `aiwg dataset plan --file <plan-input.json> --json`. Require
complete bounded enumeration of affected canonical and derived artifacts,
retention/legal-hold checks, tombstones by default, rollback limits, and a
reviewed bulk threshold. Dataset Policy Reviewer approval must match the exact
plan digest.

Delegate only through `aiwg dataset ingest` with the exact retirement plan
digest, idempotency key, approval IDs, preview digest, and threshold.
Never delete directly. Preserve canonical material unless explicitly and
separately authorized. Finish with `aiwg dataset verify <run-ref> --json` and a
reconciliation/evidence handoff.