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Agent Skill · 研究检索

review-chamber(审查室)

review-chamber 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。

review-chamber 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,权限为接触敏感数据;许可证为 MIT,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 44,915。

总安装 881周安装 36GitHub Stars 264下载 282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
MIT

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:review-chamber(审查室)
来源仓库:https://github.com/athola/claude-night-market
仓库路径:skills/review-chamber
安装命令:
npx skills add https://github.com/athola/claude-night-market --skill review-chamber
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/athola/claude-night-market --skill review-chamber

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。

review-chamber 用于信息查找、检索与筛选,支持特定领域内容探索。适用于 Codex、Claude、Cursor、Gemini CLI 中的研究检索任务。通过 npx 命令从 GitHub 仓库安装该技能。安装前需评估仓库维护状态及潜在的操作风险。建议查阅原始文档以确认其在具体场景中的应用方式。

来源仓库内路径:skills/review-chamber

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/athola/claude-night-market --skill review-cham…;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

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

review-chamber 怎么安装?

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

review-chamber 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。

review-chamber 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

review-chamber 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

review-chamber 用的人多吗?

公开数据是累计安装 881 次,近一周安装 36 次,下载 282 次,GitHub 264 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。

review-chamber 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
review-chamber

审查室 · 本页

881264接触敏感数据MIT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

Table of Contents

PR Review Chamber Skill

Capture, organize, and retrieve knowledge from PR reviews within project memory palaces.

When To Use

  • Capturing PR review knowledge for future reference
  • Building review pattern libraries from past reviews

When NOT To Use

  • Quick self-reviews of trivial changes
  • Automated CI checks that cover the review scope

Overview

The Review Chamber is a dedicated room within each project palace that stores valuable knowledge extracted from PR reviews. It transforms ephemeral PR discussions into persistent, searchable institutional memory.

Room Structure

review-chamber/
├── decisions/      # Architectural choices from PR discussions
├── patterns/       # Recurring issues and their solutions
├── standards/      # Quality bar examples and coding conventions
└── lessons/        # Post-mortems and learnings

Verification: Run the command with --help flag to verify availability.

Workflow Phases

Phase 1: Knowledge Detection

After a PR review completes, evaluate findings for knowledge capture:

## Knowledge Detection Checklist

For each finding from sanctum:pr-review, evaluate:

- [ ] **Novelty**: Is this a new pattern or first occurrence?
- [ ] **Applicability**: Will this affect future PRs in this area?
- [ ] **Durability**: Is this architectural (capture) or tactical (skip)?
- [ ] **Connectivity**: Does it link to existing palace rooms?

Verification: Run the command with --help flag to verify availability.

Phase 2: Classification

Route findings to appropriate subrooms:

Finding TypeTarget RoomCriteria
Architectural choicedecisions/BLOCKING + architectural context
Recurring issuepatterns/Seen before or likely to recur
Quality examplestandards/Exemplifies coding standards
Learning/insightlessons/Retrospective or post-mortem

Phase 3: Capture

Create structured entry with:

---
source_pr: "#42 - Add authentication"
date: 2025-01-15
participants: [author, reviewer1, reviewer2]
palace_location: review-chamber/decisions
related_rooms: [workshop/auth-patterns, library/security-adr]
tags: [authentication, jwt, security]
---

## Decision Title

### Decision
Chose JWT tokens over server-side sessions.

### Context (from PR discussion)
- Reviewer asked: "Why not use sessions?"
- Author explained: stateless scaling requirements
- Discussion refined: added refresh token rotation

### Captured Knowledge
- **Pattern**: JWT + refresh tokens for stateless auth
- **Tradeoff**: Complexity vs. horizontal scaling
- **Application**: Use for all API authentication

### Connected Concepts
- [[auth-patterns]] - Updated with JWT best practices
- [[security-adr-003]] - Referenced this decision

Verification: Run the command with --help flag to verify availability.

Phase 4: Integration

After capture, update related palace rooms:

  1. Add bidirectional links to related entries
  2. Update tags in project palace index
  3. Notify if this contradicts existing entries

Usage Examples

Capture After PR Review

# Automatic: sanctum:pr-review triggers capture
/pr-review 42
# → Review posted to GitHub
# → Knowledge capture evaluates findings
# → Significant decisions stored in review-chamber

# Manual: Explicitly capture from PR
/review-room capture 42 --room decisions

Verification: Run the command with --help flag to verify availability.

Search Past Decisions

# Find authentication decisions
/review-room search "authentication" --room decisions

# Find patterns in a specific area
/review-room search "error handling" --room patterns --tags api

# List recent entries
/review-room list --limit 10 --room standards

Verification: Run the command with --help flag to verify availability.

Surface Relevant Knowledge

When starting work in a code area:

## Relevant Review Knowledge

Starting work in `auth/` directory...

**Past Decisions:**
- [#42] JWT token decision → decisions/jwt-over-sessions
- [#67] Rate limiting pattern → patterns/api-throttling

**Quality Standards:**
- [#55] Error response format → standards/api-errors

**Known Patterns:**
- [#38] Token refresh edge case → patterns/token-refresh-race

Verification: Run the command with --help flag to verify availability.

Integration Points

With sanctum:pr-review

The review-chamber integrates after Phase 6 (Generate Report):

**Verification:** Run the command with `--help` flag to verify availability.
Phase 6: Generate Report
    ↓
[HOOK] Evaluate findings for knowledge capture
    ↓
    For each significant finding:
    ├── Classify into room type
    ├── Create ReviewEntry
    ├── Add to project palace
    └── Update connections
    ↓
Phase 7: Post to GitHub

Verification: Run the command with --help flag to verify availability.

With knowledge-intake

Uses the same evaluation framework:

CriterionWeightPR Review Application
Novelty25%New pattern or first occurrence
Applicability30%Affects future PRs in this area
Durability20%Architectural vs tactical
Connectivity15%Links to existing rooms
Authority10%Senior reviewer or domain expert

With knowledge-locator

Extends search to include review-chamber:

python scripts/palace_manager.py search "authentication" \
  --palace project-name \
  --room review-chamber \
  --type semantic

Verification: Run python --version to verify Python environment.

Evaluation Rubric

Worth Capturing (Score ≥ 60)

  • Architectural decisions with documented rationale
  • Recurring patterns seen in 2+ PRs
  • Security/performance critical findings
  • Domain knowledge that explains business logic
  • Convention changes that affect future code

Skip (Score < 60)

  • One-off tactical fixes
  • Style preferences without rationale
  • Obvious bugs without pattern
  • External dependency issues
  • Temporary workarounds

CLI Reference

# Capture knowledge from PR
/review-room capture <pr_number> [--room <room_type>] [--tags <tags>]

# Search review chamber
/review-room search "<query>" [--room <room_type>] [--tags <tags>]

# List entries
/review-room list [--room <room_type>] [--limit N]

# View entry details
/review-room view <entry_id>

# Export for documentation
/review-room export [--format markdown|json] [--room <room_type>]

# Statistics
/review-room stats [--palace <palace_id>]

Verification: Run the command with --help flag to verify availability.

Best Practices

  1. Capture decisions immediately - Context is freshest right after review
  2. Link related entries - Build the knowledge graph
  3. Use consistent tags - Enable cross-project discovery
  4. Review periodically - Prune outdated entries
  5. Surface proactively - Show relevant knowledge when starting related work

Module Reference

  • See modules/capture-workflow.md for detailed capture process
  • See modules/evaluation-criteria.md for knowledge worth assessment
  • See modules/search-patterns.md for query optimization

平台分布

Claude Code

28.93%
按下载量换算82

OpenCode

25.87%
按下载量换算73

Cursor

15.95%
按下载量换算45

Codex

11.31%
按下载量换算32

Antigravity

7.36%
按下载量换算21

Gemini CLI

3.48%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。

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