Skip to content
Development
Skill

/dataset-retire

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

From plugin
aiwg
211200 skills199 agents26 commands
Install
$ npx -y skills add jmagly/aiwg --skill dataset-retire --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/dataset-retire

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

dataset-retire.SKILL.md
namespace: aiwg
name: dataset-retire
description: Plan and delegate safe dataset retirement, tombstoning, derived-artifact cleanup, and reconciliation.
version: 1.0.0
platforms: [all]
aliases: [remove dataset, decommission index, dataset cleanup]
triggers: [retire this dataset, remove this index safely, delete derived dataset artifacts, reconcile dataset deletion, decommission this source]

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.

Ships withaiwg

Reusable project context and specialist workflows for the AI tools you already use. Plan software, coordinate specialist reviews, prepare campaigns, investigate incidents, organize research, curate media, and maintain operational knowledge.

Get the whole plugin

Other skills on aiwg.