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Agent Skill · 研究检索

plan-review(计划审查)

plan-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

plan-review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 59,696。

总安装 380周安装 16GitHub Stars 450下载 133核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:plan-review(计划审查)
来源仓库:https://github.com/ag-grid/ag-charts
仓库路径:skills/plan-review
安装命令:
npx skills add https://github.com/ag-grid/ag-charts --skill plan-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ag-grid/ag-charts --skill plan-review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

plan-review 采用多视角并行评审机制检验实施方案完整性与可验证性。适用于大型功能模块上线前的交叉验证与风险点排查任务。支持快速模式和外部工具协同,灵活适配不同评审强度需求。输入需明确计划文件路径或通过上下文自动定位最近方案文档。默认包含 Devil's Advocate 反方论证环节以增强结论稳健性。

来源仓库内路径:skills/plan-review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ag-grid/ag-charts --skill plan-review;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

plan-review 怎么安装?

在终端执行 npx skills add https://github.com/ag-grid/ag-charts --skill plan-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

plan-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

plan-review 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

plan-review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

plan-review 用的人多吗?

公开数据是累计安装 380 次,近一周安装 16 次,下载 133 次,GitHub 450 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

plan-review 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
plan-review

计划审查 · 本页

380450只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Plan Review Prompt

You are a plan reviewer. Review implementation plans for completeness, correctness, and verifiability using a multi-agent approach with parallel review perspectives.

Input Requirements

User provides one of:

  • Explicit plan file path: /plan-review path/to/plan.md
  • Auto-detect from context: /plan-review (looks for recent plans)

Optional flags:

  • --quick - Fast review with fewer agents (3-4 vs 6-8)
  • --thorough - Comprehensive review (default)
  • --external - Include external tools (Codex/Gemini) if available
  • --no-devils-advocate - Skip the Devil's Advocate review pass (runs by default)

Sub-Documents

Load sub-documents progressively based on the review mode and phase.

DocumentPurposeWhen to Load
agent-prompts-quick.mdAgent prompt templates for quick modeQuick mode (--quick)
agent-prompts-thorough.mdAgent prompt templates for thorough modeThorough mode (default)
output-format.mdReport template and output structurePhase 3 (Synthesis)
discovered-work.mdDiscovered Work Protocol for sub-agentsInclude in all sub-agent prompts
external-tools.mdCodex/Gemini integrationOnly with --external flag
agents/devils-advocate.mdDevil's Advocate adversarial review agentDefault (skip with --no-devils-advocate)

Execution Phases

Phase 0: Plan Detection & Mode Selection

  1. Detect plan file: # If explicit path provided, use it # Otherwise, check common locations: # 1. ${CLAUDE_CONFIG_DIR:-~/.claude}/plans/ (recent files) # 2. Current conversation context # 3. node_modules/.cache/plans/ # List recent plan files find "${CLAUDE_CONFIG_DIR:-$HOME/.claude}"/plans node_modules/.cache/plans -name "*.md" -mtime -7 2>/dev/null | head -10
  2. Determine review mode: Flag Mode Agents Use Case --quick Quick 3-4 Fast feedback, simple plans --thorough (default) Thorough 6-8 Comprehensive review, complex plans
  3. Extract original request/specification: Critical: The original user request is the source of truth for coverage verification. Store as ${ORIGINAL_REQUIREMENTS} for use by review agents. If no original request can be located:

- Search conversation context or plan metadata for the original user request or linked specification - If the plan embeds or references the original request, extract it - Otherwise, check the conversation history that preceded the plan - Decompose the original request into a numbered requirements checklist — discrete, verifiable asks - Each requirement should be atomic (one testable assertion per item) - Flag as IMPORTANT: "Plan does not embed or reference the original request/specification" - Recommend the plan include a Source Request section quoting or summarising the original ask - Fallback: Derive ${ORIGINAL_REQUIREMENTS} from the plan's stated goals/objectives instead — decompose them into the same numbered checklist format. Note in the output that coverage assessment is based on plan goals (lower confidence) rather than the original request

  1. Extract and validate intent: Critical: Intent clarity is vital for successful execution. Extract: If intent is unclear or missing from the plan, flag as CRITICAL issue. Compare against original request: Does the plan's stated intent align with what the user actually asked for? Flag divergence as CRITICAL — the plan may have drifted from the original ask or reinterpreted requirements.

- Core intent: The fundamental "why" behind this plan (1-2 sentences) - Success definition: What does "done well" look like? - Non-goals: What this plan explicitly does NOT aim to achieve - Constraints: Boundaries that must be respected

  1. Parse plan structure: Extract from the plan file:

- Goals/objectives: What the plan aims to achieve - Tasks/tasks: Individual implementation tasks - Files to modify: Target files for changes - Verification criteria: How success is measured - Dependencies: Relationships between tasks

  1. Build task dependency graph: Analyse task dependencies:

- Explicit dependencies (task X requires task Y) - Implicit dependencies (file modifications, data flow) - Identify parallelisation opportunities

Phase 1: Parallel Review Agents

Launch specialised review agents based on mode. Load the appropriate agent prompts sub-document:

  • Quick mode: Read .rulesync/skills/plan-review/agent-prompts-quick.md
  • Thorough mode: Read .rulesync/skills/plan-review/agent-prompts-thorough.md

Include the Discovered Work Protocol from .rulesync/skills/plan-review/discovered-work.md in all sub-agent prompts.

Quick Mode (3-4 agents)
┌─────────────────────────────────────────────────────────────┐
│                    QUICK MODE AGENTS                         │
├─────────────────────────────────────────────────────────────┤
│ 1. Intent & Completeness Reviewer                            │
│    - Is core intent clearly stated and propagated?          │
│    - Does plan intent match the original request intent?    │
│    - Are all original requirements covered by plan tasks?   │
│    - Edge cases: What could go wrong?                       │
├─────────────────────────────────────────────────────────────┤
│ 2. Verification Reviewer                                     │
│    - Testability: Can each task be verified?                │
│    - Success criteria: Are they measurable?                 │
│    - Evidence: How will completion be demonstrated?         │
├─────────────────────────────────────────────────────────────┤
│ 3. Parallelisability Analyser                               │
│    - Dependencies: What must run sequentially?              │
│    - Concurrency: What can run in parallel?                 │
│    - Agent topology: Optimal execution pattern              │
│    - Intent in sub-agent prompts: Is WHY conveyed?          │
├─────────────────────────────────────────────────────────────┤
│ 4. Devil's Advocate (default, skip with --no-devils-advocate)│
│    - Challenge: Is this the right approach?                 │
│    - Assumptions: What if key assumptions are wrong?        │
│    - Necessity: Could tasks be removed or deferred?         │
│    - Adversary: What is the most likely point of failure?   │
└─────────────────────────────────────────────────────────────┘
Thorough Mode (6-8 agents)
┌─────────────────────────────────────────────────────────────┐
│                   THOROUGH MODE AGENTS                       │
├─────────────────────────────────────────────────────────────┤
│ 1. Intent Reviewer (CRITICAL - runs first)                   │
│ 2. Completeness & Specification Coverage Reviewer            │
│ 3. Technical Reviewer                                        │
│ 4. Verification Reviewer                                     │
│ 5. Risk Reviewer                                             │
│ 6. Parallelisability Analyser                               │
│ 7. Devil's Advocate (default, skip with --no-devils-advocate)│
│ 8. External Reviewer (optional, --external flag)            │
└─────────────────────────────────────────────────────────────┘

Phase 2: Agentic Execution Analysis

After gathering review findings, analyse the plan for optimal agentic execution.

Agentic Patterns to Assess
PatternDescriptionWhen to Recommend
Simple ExecutionMain agent executes directlySimple, low-risk tasks
Sub-agent DelegationLaunch dedicated sub-agentComplex tasks requiring focus
Sub-agent + VerifyImplementation + verification agentTasks with testable outcomes
Iterate-until-verifiedLoop: implement → verify → fixTasks with clear success criteria
Parallel Fan-outLaunch N agents for independent workTasks with no dependencies
Orchestrated PipelineChained agents with handoffsSequential dependent tasks
Tree ExecutionParent spawns children, aggregatesDivide-and-conquer tasks
Dependency Detection

Analyse for:

  1. File-level dependencies: Does task B modify files created by task A?
  2. Data-flow dependencies: Does task B need outputs from task A?
  3. Implicit ordering: Build before test, create before modify, format before commit

Phase 3: Synthesis

Load .rulesync/skills/plan-review/output-format.md for the report template.

Aggregate findings from all review agents:

  1. Categorise by severity: Critical / Important / Minor
  2. Consolidate duplicates — merge similar findings from different reviewers
  3. Generate actionable recommendations — specific changes, priority order
  4. Build specification coverage analysis — traceability matrix, coverage metrics
  5. Aggregate discovered tasks — call TaskList, triage, include in report

Phase 4: Interactive Resolution (Optional)

If issues found, present to user for iterative refinement.


Devil's Advocate Mode (Default)

By default, an additional adversarial review pass runs after the standard review agents complete. This mode challenges assumptions, stress-tests the plan's approach, and questions whether the proposed tasks are the right ones. Pass --no-devils-advocate to skip it.

Workflow

  1. Run the standard review agents first. Complete Phase 1 (parallel review agents) and collect all findings.
  2. Spawn a sub-agent with the Devil's Advocate instructions. Use the Agent tool to spawn a sub-agent with:

- The full instructions from agents/devils-advocate.md. - The plan content, original requirements, and a summary of the standard review findings (so the DA can challenge those too).

  1. Merge findings from both passes.

- Combine standard review findings with Devil's Advocate findings (prefixed with [DA]). - Deduplicate: if both passes flag the same plan element for the same issue, keep the higher-severity version and note it was flagged by both passes. - Add a ## Devil's Advocate Findings section in the output report after the standard findings sections.

  1. Update the assessment. If the Devil's Advocate pass surfaces CRITICAL or IMPORTANT issues not found in the standard review, adjust the overall assessment and recommendations accordingly.

Usage Examples

# Thorough review (default)
/plan-review

# Quick review for faster feedback
/plan-review --quick

# Explicit plan file
/plan-review path/to/plan.md

# Include external tools if available
/plan-review --external

Integration with Other Commands

  • Before implementation: Run /plan-review to validate the plan
  • During implementation: Run /plan-implementation-review to track progress
  • After implementation: Run tests and verification tasks from the plan

Cache Location

Review results are cached for resumability:

node_modules/.cache/plan-reviews/
├── {plan-name}-{timestamp}.json    # Raw agent findings
├── {plan-name}-report.md           # Generated report
└── metadata.json                   # Review session metadata

平台分布

Codex

36.69%
按下载量换算49

Claude

28.22%
按下载量换算38

Cursor

18.08%
按下载量换算24

Gemini CLI

8.47%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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