Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ali-demirbas/claude-lifecycle/plugin install claude-lifecycleWrote 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/ali-demirbas/claude-lifecycle/lifecycle-results)<a href="https://agentmods.dev/skills/ali-demirbas/claude-lifecycle/lifecycle-results"><img src="https://agentmods.dev/badge/skills/ali-demirbas/claude-lifecycle/lifecycle-results/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/ali-demirbas/claude-lifecycle/lifecycle-results"><img src="https://agentmods.dev/badge/skills/ali-demirbas/claude-lifecycle/lifecycle-results.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00107 | $0.01971 |
| Opus 5 | $0.00053 | $0.00986 |
| Sonnet 5 | $0.00021 | $0.00394 |
| Haiku 4.5 | $0.00011 | $0.00197 |
Grade A, and why
lifecycle-results 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 8d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lifecycle Results — Closing the Loop
The engine generates journeys and KPIs; this skill reads what actually happened and feeds it back. It recommends — promotion, demotion, and deletion are always the user's call. Doctrine: ${CLAUDE_PLUGIN_ROOT}/knowledge/measurement.md — every rule there binds this skill.
When NOT to use this
- No performance data exists yet — the journey hasn't launched, or has launched but no measurement window has closed — there's nothing to ingest; using this skill early just returns "insufficient data" against every journey instead of a real verdict.
- The ask is whether the CRM setup fires correctly BEFORE launch — that's
lifecycle-qa(trigger correctness), not this skill (outcome measurement after real users have gone through it). - The ask is a structural or methodological review of a journey's design — that's
lifecycle-audit. This skill evaluates measured outcomes against the incrementality doctrine; it doesn't review the design itself.
Step 1 — Ingest
Accept results in any form the user has: CSV export, pasted table, or plain description. Per journey, collect what exists:
- entered / exposed / control counts, conversions per group, window covered
- per-step diagnostics (opens, clicks, unsubscribes) if available
- which copy variant ran (A/B) and its
strategy/hypothesislabels from the copy output
Missing fields are recorded as missing — never interpolated.
Step 2 — Validate before judging (the gate)
Apply measurement.md's honesty rules before any verdict:
- Sample size: control group below ~200 conversions → verdict is capped at "insufficient data — extend window / reduce holdout / keep running", regardless of how bad the lift looks. Zero lift on an underpowered test means unmeasured, not failed.
- Window: results read before the journey family's measurement window closed (recovery 1–7d, activation 7–14d, winback 30–90d) are provisional.
- Contamination check: ask whether holdout users could have been reached by an overlapping journey (portfolio conflict review names the overlaps).
- External factors: price changes, PR spikes, seasonal peak (playbook Seasonality section) — flag if the window overlaps one; attributed numbers inflate on elevated baselines.
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.
- 8d ago First seen · 78 lines · 107 tokens per session scan A dbddc6e94622
lifecycle-results is a skill published in the GitHub repository ali-demirbas/claude-lifecycle (2 stars, last pushed 21d ago), licensed MIT. It adds 107 tokens to every session and 1,971 once invoked, about $0.0005 per session on Opus 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 2026-08-31.
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