Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bdfinst/agentic-dev-team --skill artifact-lifecyclegit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bdfinst/agentic-dev-team/artifact-lifecycle)<a href="https://agentmods.dev/skills/bdfinst/agentic-dev-team/artifact-lifecycle"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/artifact-lifecycle/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bdfinst/agentic-dev-team/artifact-lifecycle"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/artifact-lifecycle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 11 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.01031 |
| Opus 5.5 | $0.00038 | $0.00412 |
| Sonnet 5.5 | $0.00019 | $0.00206 |
| Haiku 4.5 | $0.00009 | $0.00103 |
Grade A, and why
artifact-lifecycle scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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):
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 128 lines · 94 tokens per session scan A fd268f1c5998
artifact-lifecycle is a skill published in the GitHub repository bdfinst/agentic-dev-team (295 stars, last pushed 4d ago), licensed MIT. It adds 94 tokens to every session and 1,031 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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