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launch-retro-analyzer

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Use when the user asks to "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill

launch/prove/launch-retro-analyzer/SKILL.md

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Nov 12, 2026
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Apache-2.0

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# Launch Retro Analyzer

Runs the structured D1/W1/M1 retrospective after a launch: the per-channel actual-vs-target read, the 5-Whys on the single largest miss, the keep / kill / change call per channel, and the 3-5 learnings that change the next launch. It sits in the **Prove** phase of the RAMP loop (Research → Assemble → Mobilize → Prove) and feeds the RAMP `P` retro sub-items — retro completed (channel actual-vs-target, 5-Whys on misses, keep/kill) and learnings promoted to memory + the launch-registry outcome snapshot — plus the `P` attribution discipline that own UTM-attributed analytics, not platform self-reported numbers, are the truth column. See [ramp-benchmark.md](../../../references/ramp-benchmark.md).

Only [launch-readiness-auditor](../../mobilize/launch-readiness-auditor/SKILL.md) runs a typed lifecycle RAMP profile; this skill owns the retro evidence and hands off.

**Scope guard**: this skill runs the retro only. It does **not** compute return math — CPA / ROI / payback is [roi-calculator](../../../influencer/report/roi-calculator/SKILL.md); does not write the stakeholder-facing report — that is [report-generator](../../../influencer/report/report-generator/SKILL.md); does not run metric deep-dives or anomaly analysis — that is [performance-analyzer](../../../influencer/report/performance-analyzer/SKILL.md); does not track the live T-0→T+30 window ([launch-monitor](../launch-monitor/SKILL.md)) or triage feedback ([launch-feedback-synthesizer](../launch-feedback-synthesizer/SKILL.md)); and it never writes `memory/launch-registry/` records directly — [launch-registry](../../../protocol/launch-registry/SKILL.md) is the sole writer; this skill submits the outcome snapshot to `memory/events/launches.ndjson` via an authorized `operation: propose` request to `registry-events.py` only.

## Quick Start

```
Run a W1 retro on our [product] launch. Targets: [D0/W1 KPIs]. Here is the GA4 UTM export and the platform dashboards.
```
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