review-plan

作者: microsoft

審查由 Plan 代理生成的實作計畫。在移交給實作之前審查計畫至關重要——計畫常有漏洞、…

npx skills add https://github.com/microsoft/vscode-team-kit --skill review-plan

Skill: Review Plan

Your goal is to CRITICALLY review the given implementation plan. Provide thorough, constructive feedback that enhances the plan's quality and likelihood of successful execution and solving the stated goal.

Fan out parallel read-only subagents, each assigned a different plan-review area, then synthesize the highest-signal findings. Each subagent goes deep on one area, catching gaps a single pass misses.

Review Areas

Pick 2–4 areas based on the plan's complexity and risk profile.

AreaFocus
CompletenessMissing requirements, unaddressed edge cases, gaps between the stated goal and proposed steps, unclear expected outcomes
GroundingTechnical soundness and factual accuracy — references to nonexistent or deprecated APIs, hallucinated functions, incorrect codebase assumptions, outdated versions. Use web search to validate uncertain claims. Suggest alternative approaches when the plan is fundamentally wrong
SequencingDependency correctness between steps, parallelism opportunities missed, blocking-step identification, optimal ordering
ScopeOver-engineering, gold-plating, scope creep or under-specification, scope disproportionate to value delivered
VerificationAre verification steps specific, actionable, and covering the riskiest parts of the change? Missing test strategies
RiskUnaddressed failure modes, migration risks, backward compatibility gaps, missing rollback strategy

Workflow

1 — Scope

  • Look for a plan in session memory at /memories/session/plan.md first.
  • If no session plan exists, check for a plan file the user points to, or a plan visible in the conversation context.
  • If there is nothing to review, ask the user to run the Plan agent first or point at a plan file.

2 — Fan Out

Launch 2–5 parallel subagents using the area prompts below. Each subagent works in isolation — do not share one area's findings with another before synthesis.

Each gets a self-contained prompt with its area, the plan location, and the return format. Subagents read the full plan from session memory themselves. Subagents may surface findings their area doesn't explicitly list — don't constrain them to only the listed focus items.

3 — Synthesize

When all subagents return:

  1. Deduplicate findings that overlap across areas (e.g., a feasibility gap that also shows up as a sequencing problem).
  2. Order by severity: missing requirements > incorrect assumptions > sequencing errors > scope issues > weak verification > minor risks.
  3. Apply the signal filter — drop anything that wouldn't actually cause problems during implementation.
  4. If no blocking issues survive, say so and note any areas where the plan could be strengthened.

4 — Save Findings

Always save the synthesized findings to session memory at /memories/session/plan-review.md. This makes them available for follow-up turns, plan revision, and cross-referencing during implementation.

5 — Revise or Report

  • Review-only: if the user said "only review", "just review", or "read-only", stop after reporting.
  • Default (review-and-revise):
    1. For each actionable finding, propose a specific revision to the plan — what to add, remove, reorder, or clarify.
    2. Apply revisions to the plan in session memory (/memories/session/plan.md), preserving the plan's existing structure.
    3. After revising, re-read the updated plan to confirm the revisions are coherent.
    4. Report what was revised and any remaining items that need the user's input or a decision.

Signal Filter

Before reporting a finding, ask: Does this change what a developer would actually do — or how likely the plan is to succeed? Ground every finding in something observable: a file that doesn't exist, an API that behaves differently, a requirement the steps don't cover, a sequence that creates rework.

If a concern is speculative, cosmetic, or unrelated to the plan's goal, leave it out.

Area Prompt

Each subagent gets this prompt with {AREA} and {FOCUS} filled in from the Review Areas table.

You are a focused plan-review subagent. Your area is: {AREA}

## Where to find the plan
The plan is in session memory at `/memories/session/plan.md`. Read it with your memory tools first. Then explore the codebase to validate the plan's assumptions — check that referenced files, functions, and patterns actually exist.

Focus on: {FOCUS}

Use your tools to read the full plan, inspect the codebase, verify assumptions, and run existing tests or check lint/compile errors for evidence. Use web search to validate uncertain API or version claims.

Rules:
- Stay read-only. Do not edit files.
- Only flag issues that would change what a developer actually does or how likely the plan is to succeed.
- Do not report issues outside your area, but do surface unexpected findings within it.
- Do not rewrite the plan — describe the problem and why it matters.
- Keep your response short. No preamble, no formatting commentary.

Return format:

**Area**: {AREA}

**Findings** (0–5 items, severity order):
- One-sentence description. Why it matters. Evidence from the codebase if applicable.

If the plan is sound for your area: "No issues found in {AREA}."

來自 microsoft 的更多技能

oss-growth
microsoft
開源增長駭客角色
agent-framework-azure-ai-py
microsoft
使用Microsoft Agent Framework Python SDK(agent-framework-azure-ai)构建Azure AI Foundry代理。适用于使用AzureAIAgentsProvider创建持久化代理、使用托管工具(代码解释器、文件搜索、网络搜索)、集成MCP服务器、管理对话线程或实现流式响应。涵盖函数工具、结构化输出和多工具代理。
development
airunway-aks-setup
microsoft
在AKS上設定AI Runway——從裸叢集到執行模型。涵蓋叢集驗證、控制器安裝、GPU評估、供應商設定及首次部署。時機:「設定AI Runway」、「上線AKS叢集」、「安裝AI Runway」、「airunway設定」、「部署模型至AKS」、「在AKS上進行GPU推論」、「在AKS上設定KAITO」、「在AKS上執行LLM」、「在AKS上使用vLLM」、「在AKS上設定模型服務」、「AI Runway控制器」。
devops
appinsights-instrumentation
microsoft
使用Azure Application Insights檢測Web應用程式的指南。提供遙測模式、SDK設定與組態參考。適用時機:如何檢測應用程式、App Insights SDK、遙測模式、什麼是App Insights、Application Insights指南、檢測範例、APM最佳實踐。
devops
applicationinsights-web-ts
microsoft
使用Application Insights JavaScript SDK(@microsoft/applicationinsights-web)為瀏覽器/Web應用程式進行檢測。適用於真實使用者監控(RUM)——頁面檢視、點擊、AJAX/fetch依賴、例外、自訂事件,以及與後端OpenTelemetry追蹤關聯的瀏覽器端GenAI代理追蹤。涵蓋SDK載入器指令碼與npm設定、框架擴充(React、React Native、Angular)、點擊分析、遙測初始化器,以及從瀏覽器發出的代理/工具/模型span的OTel GenAI語意慣例。
devops
azure-ai-anomalydetector-java
microsoft
使用適用於 Java 的 Azure AI 異常偵測器 SDK 建置異常偵測應用程式。在實作單變量/多變量異常偵測、時間序列分析或 AI 驅動監控時使用。
development
azure-ai-language-conversations-py
microsoft
使用 azure-ai-language-conversations Python SDK 實作對話語言理解(CLU)。當使用 ConversationAnalysisClient 分析對話意圖與實體、建置 NLP 功能,或將語言理解整合至應用程式時使用。
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python。用於機器學習工作區、作業、模型、資料集、計算資源與管線。 觸發詞:「azure-ai-ml」、「MLClient」、「workspace」、「model registry」、「training jobs」、「datasets」。
development