Agent Skills
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analyze-performance-diagnose
GitHub分析性能指标异常，通过测试数据断点、排查日志与竞品动态，解释核心指标波动原因及置信度，并检查落地页匹配度。
触发场景
需要诊断营销活动或产品性能中的指标异常
需要解释关键业务指标（如ROAS、转化率）大幅波动的原因
安装
npx skills add gooseworks-ai/goose-skills --skill analyze-performance-diagnose -g -y
SKILL.md
Frontmatter
{
"name": "analyze-performance-diagnose",
"version": "0.1.1",
"description": "Step of the analyze-performance playbook: flags tracking breaks with fixes and explains each big metric move with evidence, confidence and ruled-out causes. Run analyze-performance instead; not for direct use."
}
Plumbing and the why (atom)
Load: ../analyze-performance/references/diagnosis.md.
Inputs: the clean dataset; the overclaim ratio and its trend; the change log (decisions.md); push failures/disapprovals reported by run-paid-campaigns or the marketer; the competitor watch digest; research-market's "What people are saying" section (newest research/market/<D>-read.md; check its window); the promo calendar and stock notes from the brief; destination URLs of top ads.
Do:
- Plumbing: test each break signature (ratio jump/collapse, zero-conversion days with spend, ROAS spike with flat orders, LPV/click drop, UTM traffic missing). For each break: symptom, likely location, what to check, the fix when identifiable, what it blocks. Mark affected numbers suspect.
- For each metric that moved materially at equal maturity: read the change log, check noise, mix shift, breakdown effect and denominator changes, then walk the cause checklist in order. One piece of evidence per named cause; confidence; ruled-out and unconfirmed causes listed.
- Page/message match for the top 2–3 winners and losers (open the page if the host can browse; else ask for a screenshot): product, promise, offer, price, stock.
Output: the report's Plumbing and Why-it-moved sections, and mismatches to note.
版本历史
- 1add09b 当前 2026-11-02 21:49
