lifecycle-results

lifecycle-results is a skill for Claude Code from ali-demirbas/claude-lifecycle. It costs 107 tokens per session (1,971 once invoked), scanned A, original, MIT.

A workflow for reviewing measured results from customer journeys, such as holdout groups, opens, and conversions. It compares those results with the project's measurement rules and recommends whether each journey should be kept, promoted, reduced, or stopped.

In plain words
What is it for?
Importing results from CSV files, tables, or descriptions; evaluating journey performance; recommending next actions; and maintaining a failed-strategies log.
Why use it?
It closes the gap between launching a campaign journey and learning whether it actually worked, while recording failed approaches so they are not proposed again.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the claude-lifecycle plugin — 11 skills, 4 agents, 1 hook shipped together

Good fit Importing results from CSV files, tables, or descriptions; evaluating journey performance; recommending next actions; and maintaining a failed-strategies log.

Compare 6 skills from other repositories ↓
Install

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.

Claude Code
/plugin marketplace add ali-demirbas/claude-lifecycle
Claude Code
/plugin install claude-lifecycle

Made for: Claude Code.

Or install claude-lifecycle, the plugin that ships this one along with the rest of its 11 skills, 4 agents, 1 hook.

Wrote 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.

agentmods badge for lifecycle-results

README.md
[![agentmods](https://agentmods.dev/badge/skills/ali-demirbas/claude-lifecycle/lifecycle-results/github.svg)](https://agentmods.dev/skills/ali-demirbas/claude-lifecycle/lifecycle-results)
Your own site
<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.

agentmods 80×15 button for lifecycle-results

Your own site · 80×15
<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>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,971 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 8d ago against content hash dbddc6e94622, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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.

skills/lifecycle-results/SKILL.md · 78 lines

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/hypothesis labels 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:

  1. 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.
  2. Window: results read before the journey family's measurement window closed (recovery 1–7d, activation 7–14d, winback 30–90d) are provisional.
  3. Contamination check: ask whether holdout users could have been reached by an overlapping journey (portfolio conflict review names the overlaps).
  4. External factors: price changes, PR spikes, seasonal peak (playbook Seasonality section) — flag if the window overlaps one; attributed numbers inflate on elevated baselines.

Read the full file on GitHub · 78 lines

Changes

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.

  1. 8d ago First seen · 78 lines · 107 tokens per session scan A dbddc6e94622

Subscribe to this mod's changes

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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