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amplitude/builder-skills

監控所有進行中與近期完成的實驗,依重要性排序,並對最有影響力的實驗進行深入分析與報告。請在使用者要求「檢查實驗」、「實驗狀態」、「實驗審查」、「哪些實驗正在執行」或需要定期實驗健康報告時使用。

builder-skills 是什麼?

這個技能專為監控與報告 Amplitude 中的實驗而設計。它能自動掃描所有進行中和近期完成的實驗,根據重要性進行分類,並針對最有影響力的實驗生成詳細報告。此技能支援所有 Amplitude 專案,並能處理多個實驗群組,確保使用者能快速掌握實驗組合的整體狀態。其運作方式包括:首先透過搜尋取得實驗清單,並根據狀態(進行中、近期決定)篩選;接著,分批擷取中繼資料、指標名稱與主要結果;最後產生一份包含摘要表格、行動項目與詳細報告的完整文件。報告中會避免使用專業統計術語(如 p 值、統計檢定力),確保非專家也能輕易理解。此外,它也包含了邊界情況處理(如無實驗、樣本比例不匹配、流量分配改變),並提供明確的資料品質檢查與結果解讀框架。此技能只能執行於 Amplitude 環境中,無法在其他平台上使用。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/amplitude/builder-skills/tree/HEAD/analytics-skills/skills/monitor-experiments

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

實驗監控與報告產生器

掃描進行中與近期完成的實驗,找出需要關注的部分,並報告重要的實驗。

這是一個監控技能——保持輸出內容讓非專家也能理解。避免使用統計術語(無 p 值、無統計檢定力分析)。如需針對特定實驗進行深入分析,請改用 analyze-experiments 技能。


關鍵:管理回應大小

  1. get_experiments:每次最多 3-5 個 ID。 在擷取前,先利用 search 結果進行篩選。
  2. query_experiment 的回應很大。 只擷取 summary 物件與有效性旗標。忽略 timeseries、xValues、大量陣列。
  3. 指標名稱解析:search 不會比對查詢中的指標 ID。請使用 entityTypes: ["METRIC"]、空的 queries、limitPerQuery: 50,且範圍限於專案進行搜尋。從結果中比對 ID。

報告結構

報告分為兩個部分:

  1. 摘要與行動(頂端)——一個表格 + 行動項目。閱讀者只需看這部分就能了解全貌。
  2. 詳細資料(底部)——對需要關注的實驗進行深入探討、最近決策的摘要、監控實驗的一行說明,以及需要設定的清單。

請勿在摘要表格與詳細資料之間重複資訊。摘要表格是實驗組合狀態的單一事實來源。詳細資料則針對特定實驗進行延伸說明。


操作說明

步驟 1:情境與探索

  1. 呼叫 Amplitude:get_context。如果有多個專案,詢問要監控哪一個。
  2. 搜尋實驗:
Amplitude:search({
  entityTypes: ["EXPERIMENT"],
  appIds: [projectId],
  queries: [],
  sortOrder: "lastModified",
  sortDirection: "DESC",
  limitPerQuery: 50
})
  1. 篩選規則——包含以下實驗:
    • 正在執行且未過時: 處於執行狀態且未被標記為過時的實驗。過時的實驗已進入閒置狀態,應排除。
    • 近期決定: 已完成且已記錄決定,且在過去 14 天內有修改的實驗。這些實驗值得審查,以確認決定或分享學習成果。
  2. 排除: 草稿、已停用實驗與過時實驗。

步驟 2:擷取中繼資料、指標名稱與主要結果

  1. 以 3-5 個 ID 為一批次,呼叫 Amplitude:get_experiments(僅限步驟 1 中篩選後的集合)。
  2. 擷取:狀態、日期/持續時間、變體、指標 ID(主要且 recommendation=true)、決定、擁有者。
  3. 再次使用詳細中繼資料套用步驟 1 的篩選規則(某些欄位(如過時狀態或決定)可能只有在此處才能取得)。
  4. 透過 Amplitude:search({ entityTypes: ["METRIC"], appIds: [projectId], queries: [], limitPerQuery: 50 }) 解析指標名稱。建立 { id: name } 對應。
  5. 對於已設定指標的實驗,呼叫 Amplitude:query_experiment({ id: "<id>" })(不帶 metricIds)以取得主要指標結果與資料品質旗標。這些資料同時用於摘要表格與深入探討。

關鍵:絕對不要向使用者顯示原始指標 ID。 如果無法解析指標名稱,請根據其角色描述(例如「主要指標」、「護欄指標」)——請勿顯示像 "rrgtky08" 或 "Metric gvgb5efj" 這樣的字串。指標 ID 是內部識別碼,對人類讀者毫無意義。


步驟 3:摘要與行動

這是報告的頂端部分。應能自成體系——只看這部分的讀者就能了解全貌。

摘要表格

## 實驗監控:[專案名稱]
日期:[今天] | 專案:[名稱] ([ID])

| 實驗 | 狀態 | 持續時間 | 提升 | 判定 |
|------|------|----------|------|------|

欄位定義:

  • 實驗——人類可讀的名稱(不是 URL,不是 ID)
  • 狀態——執行中或已完成
  • 持續時間——實驗開始以來的天數
  • 提升——主要指標的相對提升(如果有),若無資料則顯示「—」。多變體實驗則顯示範圍(例如 "-17% 到 -20%")
  • 判定——該怎麼做(請參閱下方詞彙)

判定詞彙:

判定使用時機
推出主要指標顯著正向,護欄乾淨,資料品質良好
迭代正向訊號,但護欄出現衰退或資料品質有疑慮
監控執行中,尚未顯著,無須採取行動
放棄主要指標顯著負向,或存在嚴重資料品質問題
決定:推出近期完成,團隊決定推出
決定:不推出近期完成,團隊決定不推出
修正設定查詢錯誤、曝光事件損壞或流量嚴重失衡
需要指標執行中但未設定指標——無法評估
不適用調查/推播部署,非功能實驗

行動項目(緊接在表格之後)

**立即行動:**
- [實驗] — [具體行動與擁有者姓名]

**持續觀察:**
- [實驗] — [簡要狀態 + 何時回查]

**需要設定:**
- [實驗] — [缺少什麼 + 擁有者姓名]

表格中的每個實驗都應確切歸入一個行動類別。如果某類別沒有實驗,則省略該類別。


步驟 4:詳細資料

在摘要下方,按章節組織額外的詳細資訊。每個實驗只會出現在一個章節中——不重複。

4a:深入探討(需要關注的實驗)

對判定為推出、迭代或放棄的實驗進行深入探討(最多 3 個)。這些實驗有值得檢視的顯著結果。

對於每個實驗,一次性輸出完整報告:

---
## [實驗名稱]
[狀態] | [持續時間]天 | 對照組:[N] / 實驗組:[N] | [實驗連結]

資料品質(先檢查——再檢視結果):

在報告指標結果之前,先檢查資料品質。如果有嚴重問題,讀者需要在解讀任何數字之前先了解這個背景。

如果一切正常,一行說明:「資料品質檢查全部通過。」然後繼續顯示主要指標。

如果發現問題,請在主要指標之前報告:

### 資料品質:發現 [N] 個問題

樣本比例不匹配 (SRM):

  • 使用 API 回應中的 srmDetected 欄位
  • 如果 srmDetected: true:務必優先且醒目地報告
  • 報告:實際分流比例 vs. 預期分流比例,並提供具體百分比

流量分配變更:

  • 比較目前變體的權重與累積曝光分佈
  • 如果兩者不符(例如目前權重為 100/0/0,但累積分佈為 15/70/15),表示實驗中途變更了流量分配
  • 醒目地標記此情況——表示某些變體可能不再接收新流量

樣本數:

  • 每個變體少於 100:標記為不足——樣本數太少,無法得出任何結論
  • 每個變體 100–1,000:僅為方向性訊號,不足以做出有信心決定
  • 每個變體 1,000+:足以進行分析

有效性旗標——僅報告失敗的項目:

旗標失敗時的意義嚴重性
isVariancePositive = false指標資料無效——統計檢定無法執行嚴重
isConfidenceIntervalNotFlipped = false結果計算錯誤——不要相信這些數字嚴重
isMeanValid = false指標值已損壞(NaN/無限大)——無法分析嚴重
statsAssumptionsMetForWholeExperiment = false不符合統計假設——結果可能不可靠高
hasSuspiciousUplift = true異常大的效果——可能是測量錯誤,而非真實變化高
isPointEstimateInsideConfidenceInterval = false內部數學不一致——結果可能錯誤高
isStandardErrorLargeEnough = false雜訊過多,無法獲得可靠的估計值中

如果偵測到 SRM 或嚴重旗標失敗:

⚠️ 由於 [問題],以下結果應謹慎解讀。

主要指標:

### [指標名稱]:[白話判定]

| 變體 | 數值 | 提升 | 95% 信賴區間 |
|------|------|------|-------------|
| 對照組 | [X] | — | — |
| 實驗組 | [Y] | [+Z%] | [A% 到 B%] |

[一句白話解釋。]

呈現規則:

  • 請勿包含 p 值。 非專家不懂其意義。
  • 使用「不顯著」而非「沒有效果」。可能確實有影響——只是實驗在這個樣本數下無法偵測到。
  • 用白話說明發生了什麼事作為開頭。

判定用語:

  • 顯著正向——信賴區間完全高於零,正向提升
  • 顯著負向——信賴區間完全低於零,負向提升
  • 不顯著——信賴區間包含零;我們無法有信心地說存在真正的差異
  • 趨向正向/負向——方向性訊號,但信賴區間包含零;值得持續觀察

僅在提升非常小(<2%)或非常大(>20%)時,才加入一句關於實質顯著性的說明。

護欄與次要指標:

呼叫 Amplitude:query_experiment({ id: "<id>", metricIds: [...] })。

專注於捕捉衰退,而非逐一敘述每個指標。

如果沒有顯著衰退:「所有護欄與次要指標均無異常——未偵測到顯著衰退。」

如果發現顯著衰退:

- **[指標名稱]:** 顯著衰退([−X%],信賴區間:[A% 到 B%])——[一句關於影響的說明]

如果存在較大的方向性衰退(>20% 相對提升)但尚未顯著:

- **[指標名稱]:** 不顯著,但方向性為負向([−X%])——值得持續觀察

顯著性不高的小方向性變化應省略。如果指標多達 5 個以上,請註明多重比較會增加偽陽性的機率。

回饋(僅在主要指標顯著時):

使用與實驗相關的關鍵字呼叫 Amplitude:get_feedback_insights。以一行為單位報告 2-3 個主題。如果沒有相關回饋,則跳過此區段。

判定:

### 判定:[推出 / 迭代 / 監控 / 放棄]
1. [主要指標發現——一句話]
2. [品質/護欄狀態——一句話]
3. [下一步行動——一句話]

決策矩陣(內部參考,請勿輸出):

訊號推出迭代監控放棄
主要指標顯著正向 + 實質顯著顯著正向但護欄衰退尚未顯著,仍在執行顯著負向
品質全部通過次要旗標全部通過或資料不足SRM 或嚴重旗標
護欄乾淨1 項衰退需要修正乾淨或資料不足關鍵指標顯著衰退
實驗狀態已完成已完成執行中已完成或執行中

4b:執行中的實驗(監控中,無需行動)

對於判定為監控的實驗,每項提供一行狀態:

---
### 執行中的實驗

**[名稱]** — 執行中 [X] 天,對照組:[N] / 實驗組:[N]。[主要指標狀態——例如「趨向正向 (+3.3%) 但尚未顯著」]。資料品質正常。[連結]

**[名稱]** — 執行中 [X] 天,對照組:[N] / 實驗組:[N]。現在下結論還太早——[原因,例如「樣本數在 100-1,000 之間」]。[連結]

保持簡潔——每項實驗一行。在結尾處附上連結,方便任何人在 Amplitude 中進一步查看。

4c:近期決定(簡要摘要)

對於判定為決定:推出或決定:不推出的實驗:

---
### 近期決定

- **[名稱]** — 已於 [日期] [推出/回滾],經過 [X] 天。[一句關於結果或理由的說明]。[連結]

如果實驗是在沒有指標或沒有統計顯著性的情況下推出的,請簡短說明。

4d:需要設定

對於判定為修正設定、需要指標或不適用的實驗:

---
### 需要設定

- **[名稱]** — [問題說明]。擁有者:[擁有者]。
- **[名稱]** — 調查/推播部署,非功能實驗。無需分析。

每個實驗只會出現在一個詳細資料區段中。請勿將實驗同時列在摘要表格行動項目和詳細資料區段中,並提供相同的資訊——詳細資料區段是對行動項目的延伸,而非重複。


邊界情況

  • 無實驗: 清楚報告,並建議檢查其他專案
  • 無資料(<24 小時): 註明實驗剛剛開始,請在 7 天後再檢查
  • 偵測到 SRM: 在資料品質中優先說明——這可能會使其他所有結果失效
  • 10 個以上實驗: 全部列出摘要表格,深入探討前 3 個,並提供分析更多實驗的選項
  • 回應過大 / 已儲存至磁碟: 僅擷取 summary + 有效性旗標
  • 未設定指標: 列在「需要設定」區段,不進行深入探討
  • 所有實驗都已過時: 報告沒有進行中的實驗可供監控
  • query_experiment 傳回查詢錯誤: 清楚報告錯誤,並附上實驗擁有者的姓名。在摘要中標記為「修正設定」。常見原因:曝光事件屬性損壞、實驗金鑰設定錯誤。
  • 實驗中途變更流量分配: 在資料品質中標記。比較目前權重與累積曝光分佈。註明哪些變體不再接收流量。
  • 調查/推播實驗(NPS 等): 在摘要中標記為不適用。無需分析——跳過深入探討。
  • 流量嚴重失衡(例如 5%/95% 或 0%/100%): 標記為「修正設定」——沒有有意義的對照組就無法執行有效的實驗。在需要設定區段中註明擁有者。

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

amplitude/builder-skills

Performs deep analysis of a specific Amplitude chart to explain trends, anomalies, and likely drivers. Use when a metric looks unusual, investigating a spike or drop, or understanding the "why" behind numbers.

amplitude/builder-skills

Deeply analyze Amplitude dashboards by analyzing key charts, surfacing top areas for concern and takeaways, identify anomalies, then explain changes using customer feedback trends.

amplitude/builder-skills

Designs A/B tests with proper metrics and variants, analyzes running or completed experiments, and interprets results with statistical rigor. Use when setting up experiments, checking experiment status, analyzing results, or making ship decisions.

amplitude/builder-skills

Synthesizes customer feedback into actionable themes including feature requests, bugs, pain points, and praise. Use when planning product roadmap, understanding user sentiment, investigating specific issues, or preparing voice-of-customer reports.

amplitude/builder-skills

Analyze MCP server usage instrumented with Amplitude's MCP Analytics SDK: break usage and errors down by tool, read the rationales within each tool to see what callers are trying to do, and produce a prioritized write-up of actionable fixes. Use this skill whenever the user asks to understand how their MCP server is being used, what agents/users are trying to do with it, why tool calls are failing, what to fix or improve in their MCP server, or asks for an "MCP usage report", "tool error analysis", "intent analysis", "rationale clustering", or "MCP insights". Also trigger when the user mentions [MCP]-prefixed events, tool rationale, tool call errors, or just finished instrumenting their MCP server and wants to see what the data says. Requires the Amplitude MCP connector.

amplitude/builder-skills

Read lost deals and churned accounts from your CRM, extract reasons clustered by theme (missing features, pricing, competitors, UX), and write a prioritized weekly analysis with product improvement recommendations. Use before roadmap planning or to build the case for prioritizing retention work.

amplitude/builder-skills

Creates Amplitude charts from natural language descriptions, handling event selection, filters, groupings, and visualization choices. Use when you know what you want to measure but prefer not to build the chart manually.

amplitude/builder-skills

Guide an Amplitude user through building a custom agent by suggesting use cases grounded in their role and data, shaping the idea into a well-formed spec, and generating a ready-to-run Global Agent deeplink that creates it. Use to create, build, or set up a custom agent, automate a recurring analysis, or put a repeated report on a schedule.

amplitude/builder-skills

Builds comprehensive Amplitude dashboards from requirements or goals, organizing charts into logical sections with appropriate layouts. Use when creating a complete dashboard from scratch or assembling existing charts into a cohesive view.

amplitude/builder-skills

Pull Intercom tickets and Slack support messages from the past 7 days, classify each signal, enrich with CRM data (ARR, plan, renewal), score by customer value and churn risk, and output a tiered priority report saved to Drive. Use when you need a fast, data-driven view of what support signals matter most.

amplitude/builder-skills

Use this skill whenever a user wants to improve existing pages on their website to get cited more by AI models — whether they say "our pages aren't getting cited", "improve this page for AI visibility", "which of our pages should we update", "make this article more cite-worthy", "our competitors are getting cited instead of us", "update our content for AI search", or any variation where the goal is improving an existing asset rather than creating something new. This skill pulls owned pages from AI Visibility, identifies which ones have citation potential but are underperforming, compares them against the external pages that are winning citations on the same topics, and produces section-level rewrites or a full-page update — then pushes the revision to the CMS as a draft. Trigger even if the user just says "help me get cited more" or "why is [competitor] getting cited instead of us".

amplitude/builder-skills

Use this skill whenever a user wants to win AI citations on prompts that competitors currently dominate — whether they say "competitors are getting cited instead of us", "we're losing on these prompts", "how do I outrank [competitor] in AI answers", "find prompts where we should be winning", "create content to beat [competitor]", or any variation where the goal is capturing AI share on prompts a competitor currently owns. This skill pulls competitor visibility data from AI Visibility, identifies the specific prompts where competitors win and Amplitude is absent, clusters them by intent, and produces targeted comparison pages, alternatives content, or rebuttal assets — then pushes drafts to CMS. Trigger on any mention of competitor, prompt hijack, outrank, or "why is [competitor] getting cited instead of us".

amplitude/builder-skills

Use this skill whenever a user wants to turn AI Visibility data into published content — whether they say "find content gaps", "what should we write about", "which topics have low visibility", "help me get cited by AI models", "create a blog post from our AI Visibility gaps", "we're losing to competitors on these prompts", or any variation where they want to go from AI visibility weakness to a draft article, landing page, or FAQ. This skill connects directly to Amplitude AI Visibility data (topics, prompts, visibility scores, citations, competitor data, full LLM responses and sources) and produces a publish-ready content brief plus full article draft. If the user mentions CMS (WordPress, Webflow, Contentful, Sanity, HubSpot, Ghost, Shopify), also trigger this skill to push the draft directly. Trigger even if they just say something vague like "what content should we create?" in an AI Visibility context.

amplitude/builder-skills

Use this skill whenever a user wants to test content variants before publishing to find which one will get cited most by AI models — whether they say "which version of this content will perform better", "test this article before we publish", "simulate how AI will respond to this content", "which angle should we use", "generate content variants and pick the winner", "run a simulation before publishing", or any variation where the goal is data-driven content selection rather than gut-feel publishing. This skill takes an identified content opportunity, generates 2–3 distinct variants with different angles or structures, scores them against actual AI model responses from AI Visibility, references the Simulate Changes feature for pre-publish validation, and produces a clear recommendation on which variant to publish — then pushes the winner to CMS. Trigger on any mention of "simulate", "test variants", "which performs better", "A/B content", or "before we publish".

amplitude/builder-skills

Use this skill whenever a user wants to understand which external sources are being cited by AI models on topics relevant to their brand, and wants to create content that will outrank those sources — whether they say "what sources are AI models citing", "why is [third-party site] being cited instead of us", "we want to be the definitive source on X", "build something that gets cited more than G2 or TechRadar", "create an authoritative asset", or any variation where the goal is producing a new reference asset (definition page, benchmark, methodology, glossary, comparison hub) designed to beat existing top-cited sources. This skill analyzes AI Visibility source data, reverse-engineers what makes top-cited pages authoritative, and produces a superior source asset — then pushes it to CMS as a draft. Trigger on any mention of "sources", "third-party citations", "authoritative content", "definitional pages", or "outrank".

amplitude/builder-skills

Instrument a Node/TypeScript MCP server with Amplitude's @amplitude/mcp-analytics SDK so tool calls, sessions, and rationale are tracked as Amplitude events. Use this skill whenever the user wants to add Amplitude analytics to their MCP server, mentions "MCP Analytics", "@amplitude/mcp-analytics", "instrument my MCP server", "track MCP tool calls", "add rationale to my MCP tools", or wants agent traffic (Claude, Cursor, ChatGPT) attributed back to Amplitude. Also use for adding UTM tagging to MCP-returned links, or for troubleshooting identity/user_id mismatches between MCP events and web/mobile Amplitude data.

amplitude/builder-skills

Instruments a pull request with Amplitude analytics that conform to the project's existing taxonomy. Reads the tracking plan via the Amplitude MCP server (events, properties, naming conventions), analyzes the PR diff to find the few user actions genuinely worth tracking, detects the codebase's SDK and tracking patterns, and adds instrumentation that matches both. Optionally (opt-in) stages new events and properties on an Amplitude tracking-plan branch for data-governance review. Use when asked to "instrument this PR", "add analytics to this change", "add tracking", "add Amplitude events", "instrument this feature", or "what should I track here".

amplitude/builder-skills

Diagnoses product health by cross-referencing Amplitude analytics (dashboards, charts, funnels, feedback, AI agent analytics), optionally Datadog (errors, latency, stack traces), and optionally Slack (qualitative feedback, bug reports, feature requests). Identifies what's broken, what's working, and what to do about it — with root causes, not just symptoms. Use when asked to "diagnose my product", "what's going on", "product health check", "what's broken", "where are users struggling", "give me a product diagnosis", or "what should I focus on".

amplitude/builder-skills

Turn one or more meeting transcripts, notes, or Slack threads into concise takeaways and clear action items with DRIs. Works with a single meeting or a batch from the whole week.

amplitude/builder-skills

Summarizes B2B account health by analyzing usage patterns, engagement trends, risk signals, and expansion opportunities. Use for customer success reviews, renewal preparation, QBRs, or account prioritization.

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