| name | artifact-lifecycle |
| description | Report on skill and agent usage data from ~/.claude/metrics/artifact-usage.json, classifying each artifact as active, stale (>= 30 days unused), or an archive candidate (>= 90 days unused). Proposes CLAUDE.md overrides for stale artifacts and exclusions for archive candidates. Pinned skills are always exempt. Use when the user asks to "review artifact lifecycle", "find stale skills", or "/artifact-lifecycle". |
| user-invocable | true |
| allowed-tools | Read, Glob, Bash(date *), Write |
Artifact Lifecycle Management
Role: worker. Reads ~/.claude/metrics/artifact-usage.json, classifies each tracked
artifact by recency, and proposes lifecycle transitions. Never modifies files
under plugins/dev-team/ — changes land exclusively in the project CLAUDE.md.
You have been invoked with the /artifact-lifecycle command.
Steps
1. Check for usage data
Read ~/.claude/metrics/artifact-usage.json (home-scoped — never a project-scoped path).
If the file does not exist, output:
No usage data available — enable telemetry to begin tracking (see /telemetry)
Then stop. Do not produce a report.
2. Load pinned skills
Read the project CLAUDE.md (or .claude/CLAUDE.md). Extract the list of skill
names under the ## Pinned Skills section (if present). These names are exempt
from all lifecycle transitions regardless of last_used_at.
3. Classify artifacts
Get the current date:
date -u +%Y-%m-%d
For each entry in ~/.claude/metrics/artifact-usage.json, compute days_since_used as the
number of calendar days between last_used_at and today:
today=$(date -u +%s)
last=$(date -u -d "<last_used_at>" +%s 2>/dev/null \
|| python3 -c "import datetime; print(int(datetime.datetime.fromisoformat('<last_used_at>'.replace('Z','+00:00')).timestamp()))")
days_since_used=$(( (today - last) / 86400 ))
Apply thresholds (both are inclusive):
| Threshold | Classification |
|---|
days_since_used < 30 | active |
days_since_used >= 30 and < 90 | stale |
days_since_used >= 90 | archive candidate |
Skip any artifact whose name appears in the Pinned Skills list.
4. Produce report
All active
If every artifact has days_since_used < 30 (and none are stale or archived):
All tracked artifacts are active — no lifecycle changes needed.
Stop.
Stale and archive sections
Otherwise, produce a report with the following sections (only include sections
that have entries):
## Stale Skills (>= 30 days unused)
These skills have not been observed in telemetry for 30 or more days.
Proposal: add each to `## Disabled Skills` in CLAUDE.md to stop loading them
until re-enabled.
| Skill | Last used | Days since used |
|-------|-----------|----------------|
| <name> | <last_used_at> | <n> |
## Archive Candidates (>= 90 days unused)
These skills have not been observed for 90 or more days and are candidates for
permanent removal from the active set.
| Skill | Last used | Days since used |
|-------|-----------|----------------|
| <name> | <last_used_at> | <n> |
5. Propose CLAUDE.md changes (interactive)
For each Stale Skill, offer to add it to the ## Disabled Skills section in
the project CLAUDE.md. Show the proposed edit as a diff before applying.
Do not remove or modify any files under plugins/dev-team/ (the plugin cache).
All writes go exclusively to the project CLAUDE.md.
For Archive Candidates, present the list for human decision — do not auto-apply.
Pinned skills note
If any artifacts were skipped because they appear in ## Pinned Skills, note
them separately:
Pinned (excluded from all lifecycle transitions):
Constraints
- Never delete or modify files under
plugins/dev-team/ during or after execution.
All lifecycle changes land exclusively in the project CLAUDE.md.
- Report is advisory; no configuration change is applied without user approval.
- If
~/.claude/metrics/artifact-usage.json contains entries with missing or unparseable
last_used_at, log a warning and skip those entries.
