Twmd analyze

Skill frank890417/taiwan-md/.claude/skills/twmd-analyze

Rigorous data-analysis investigation via canonical ANALYSIS-PIPELINE — defends against 分析幻覺 (true-but-misleading numbers). Impact / attribution / funnel / reception / cohort analysis with confounder isolation + honest gates. TRIGGER when: user says "分析 X 有沒有改善", "這流量哪來", "before/after", "改版影響", "研究這批數據", "這個 finding 可不可信", "跑 analysis".From its SKILL.md

Install

npx -y skills add frank890417/taiwan-md --skill twmd-analyze

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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SKILL.md

2.0 KB, as published. Nobody here has run it

🧬 Taiwan.md — Analyze（極簡薄殼）

故意極簡。所有 SOP（Stage 0-7 / Hard Gate Inventory / 分析幻覺 H1-H9 目錄 / 5 mode / 深淺兩檔 / 工具盤 / §跨檔分工）100% 在 pipeline canonical。本 skill 只做三件事，不複寫 pipeline 內容（複寫 = drift = 退化）。

1. STRICT BECOME GATE（不可省）

跑 /twmd-become 完整 BECOME_TAIWANMD.md Step 0-9。分析會影響決策 / 對外 / 自己分析自己 → high-stake 強制升 Full mode，self-test 全過才動工。

2. 完整讀 ANALYSIS-PIPELINE（不可 head / tail / 取樣）

用 Read tool 一次讀完 docs/pipelines/ANALYSIS-PIPELINE.md（無 limit / offset）。照 Stage 0-7 跑，每道 hard gate 都過。

3. 執行 + 過誠實 gate 才交報告

工具盤在 scripts/tools/：ga-query.py / sc-query.py / ga-window-compare.py / referral-attribution.py / analysis-report-health.py（地基 lib/sense_client.py）。報告 ship 前 python3 scripts/tools/analysis-report-health.py {report} --tier=deep 必 PASS。Stage 7 把 finding route 到 INBOX / probe / watch，不讓報告腐爛。

鐵律：可重用的是判斷不是查詢；pipeline 防的是「真實但誤導」的分析幻覺（H1 尺度 / H2 率量 / H3 lag / H7 自我驗證）。不要用 ga4-analytics skill 的 runReport 下 filter（靜默吞 filter，REFLEXES #24）—— 一律用 ga-query.py。