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Agent Skill · 研究检索

review-orchestrator(审核协调器)

review-orchestrator 用于查找、检索和筛选相关信息,适合在 OpenClaw 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-orchestrator 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,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 9,851。

总安装 13,497周安装 546GitHub Stars 公开资料未说明下载 4,237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-0
版本
1.5.1

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-orchestrator(审核协调器)
来源仓库:https://github.com/leegitw/review-orchestrator
安装命令:
openclaw skills install review-orchestrator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install review-orchestrator

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。

协调跨认知模式的评审,从多个角度看待工作。适用于 OpenClaw 环境中的研究检索任务。通过 clawhub 安装,命令为 openclaw skills install review-orchestrator。需确认权限范围和维护状态,注意是否触发文件读写。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 OpenClaw;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 openclaw skills install review-orchestrator;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

    它需要执行命令,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-orchestrator 怎么安装?

在终端执行 openclaw skills install review-orchestrator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

review-orchestrator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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-orchestrator 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install review-orchestrator 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

review-orchestrator 是免费的吗?

来源标注的许可证是 MIT-0。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-orchestrator 用的人多吗?

公开数据是累计安装 13,497 次,近一周安装 546 次,下载 4,237 次。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-orchestrator 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,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

  • 需要执行命令,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 OpenClaw,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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-orchestrator

审核协调器 · 本页

13,497—执行命令MIT-0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

name
review-orchestrator
version
1.5.0
description
Get multiple perspectives on your work — coordinate reviews across cognitive modes
author
Live Neon <hello@liveneon.ai>
homepage
https://github.com/live-neon/skills/tree/main/agentic/review-orchestrator
repository
leegitw/review-orchestrator
license
MIT
tags
[agentic, review, orchestration, multi-perspective, code-review, quality, twin-review, feedback]
layer
review
status
active
alias
ro
metadata
openclaw
requires
config
workspace

review-orchestrator (審査)

Unified skill for selecting review types, spawning multi-perspective and cognitive review agents, and managing quality gates. Consolidates 5 granular skills into a single review system.

Trigger: レビュー要求 (review requested)

Source skills: twin-review, cognitive-review, review-selector, staged-quality-gate, prompt-normalizer

Installation

openclaw install leegitw/review-orchestrator

Dependencies:

  • leegitw/failure-memory (for context)
  • leegitw/context-verifier (for file verification)
# Install with dependencies
openclaw install leegitw/context-verifier
openclaw install leegitw/failure-memory
openclaw install leegitw/review-orchestrator

Standalone usage: Review orchestration works independently for multi-perspective reviews. Integration with failure-memory enables automatic observation recording from review findings.

Data handling: This skill operates within your agent's trust boundary. When triggered, it uses your agent's configured model for multi-perspective review orchestration. No external APIs or third-party services are called. Review results are written to docs/reviews/ in your workspace.

What This Solves

One perspective has blind spots. This skill coordinates multiple review perspectives to catch what single-pass review misses:

  1. Twin review — technical and creative perspectives for balance
  2. Cognitive modes — analyzer ("what conflicts"), architect ("how to restructure"), implementer ("how to implement")

The insight: N=2 catches more than N=1. Different perspectives see different things. Coordinate them systematically.

Note: "Cognitive modes" are review perspectives with different analytical focus, not external API calls. Mode names (analyzer, architect, implementer) describe the review approach, not specific AI models or services.

Usage

/ro <sub-command> [arguments]

Sub-Commands

CommandCJKLogicTrigger
/ro select選択context×risk→type∈{twin,cognitive,code}Explicit
/ro twin双子spawn(technical,creative)→findings[]Explicit
/ro cognitive認知spawn(modes[])→analysis[]Explicit
/ro multi双視alias for /ro twin (multi-perspective review)Explicit
/ro gate門番staged_work→pass✓∨block✗Explicit

Arguments

/ro select

ArgumentRequiredDescription
contextYesDescription of work to review
--riskNoRisk level: low, medium, high (auto-detected if omitted)

/ro twin

ArgumentRequiredDescription
targetYesFile path(s) or topic to review
--technical-onlyNoSkip creative perspective
--creative-onlyNoSkip technical perspective

/ro cognitive

ArgumentRequiredDescription
targetYesFile path(s) or topic to review
--modesNoCognitive modes: analyzer, architect, implementer (default: all)

/ro multi

Alias for /ro twin. The name "twin" refers to the dual-perspective review pattern (technical + creative), not a specific team structure. /ro multi is provided for discoverability by users unfamiliar with the "twin" terminology.

/ro gate

ArgumentRequiredDescription
stageYesStage name or number to gate
--strictNoRequire all checks pass (default: true)
--allow-minorNoAllow minor issues to pass

Core Logic

Review Type Selection

ContextRiskRecommended Review
ImplementationLow/ro twin --technical-only
ImplementationMedium/ro twin (both perspectives)
ImplementationHigh/ro twin + /ro cognitive
ArchitectureAny/ro cognitive
DocumentationAny/ro twin --creative-only
SecurityAny/ro cognitive + external review

Multi-Perspective Review

PerspectiveFocusCJK
TechnicalArchitecture, standards, patterns, security技術
CreativeUX, communication, philosophy alignment創造

Cognitive Modes

Cognitive modes provide different analytical perspectives. Modes are configurable; defaults shown below.

ModePerspectiveFocusCJK
analyzer"Here's what conflicts"Tensions, trade-offs, contradictions審碼
architect"Here's how to restructure"Architecture, patterns, organization審構
implementer"Here's how to implement"Concrete steps, complexity, path forward審実
Note: Mode names are perspective-based, not model-specific. The underlying model used for each mode is configurable (see Configuration section below).

Configuration

Configuration is loaded from (in order of precedence):

  1. .openclaw/review-orchestrator.yaml (OpenClaw standard)
  2. .claude/review-orchestrator.yaml (Claude Code compatibility)
  3. Defaults (built-in)

Cognitive Mode Interface

Each cognitive mode implements this interface:

FieldTypeRequiredDescription
idstringYesMode identifier (e.g., "analyzer", "architect")
perspectivestringYesHuman-readable perspective description
prompt_prefixstringYesPrompt prefix for this mode's analysis
model_hintstringNoOptional model preference (not enforced)

Cognitive Mode Configuration

# .openclaw/review-orchestrator.yaml
cognitive_modes:
  - id: analyzer
    perspective: "Here's what conflicts"
    prompt_prefix: "Analyze tensions, trade-offs, and conflicts in..."
    model_hint: "prefer analytical model"
  - id: architect
    perspective: "Here's how to restructure"
    prompt_prefix: "Suggest architectural improvements for..."
    model_hint: "prefer architectural model"
  - id: implementer
    perspective: "Here's how to implement"
    prompt_prefix: "Provide implementation guidance for..."
    model_hint: "prefer practical model"

Quality Gate Configuration

# .openclaw/review-orchestrator.yaml
quality_gates:
  test_command: "npm test"    # Node.js (default)
  # test_command: "go test ./..."  # Go
  # test_command: "pytest"         # Python
  # test_command: "cargo test"     # Rust
  coverage_threshold: 5       # Max allowed coverage drop (%)
  require_docs: true          # Require documentation updates

Quality Gate Checks

CheckConditionSeverity
Tests pass{test_command} exit 0Critical
Coverage maintaineddelta ≤ {coverage_threshold}%Important
No critical findingsreview.critical == 0Critical
Docs updatedchanged files have docs (if require_docs)Minor
Checks use configured values from quality_gates section. Defaults: test_command=npm test, coverage_threshold=5, require_docs=true.

Output

/ro select output

[REVIEW SELECTION]
Context: "Refactoring authentication handler"
Risk: Medium (auto-detected: changes auth code)

Recommended: /ro twin
Rationale: Medium-risk implementation benefits from both technical and creative perspectives.

Alternative: /ro cognitive (for deeper architectural analysis)

/ro twin output

[MULTI-PERSPECTIVE REVIEW INITIATED]
Target: src/handlers/auth.go
Perspectives: technical, creative

--- Technical Perspective Findings ---
Severity: important
- I-1: Missing error handling on line 45
- I-2: Consider extracting validation logic

Severity: minor
- M-1: Inconsistent naming convention

--- Creative Perspective Findings ---
Severity: minor
- M-1: Error messages could be more user-friendly
- M-2: Consider adding debug logging for operators

Verdict: Approved with conditions

/ro cognitive output

[COGNITIVE REVIEW INITIATED]
Target: docs/architecture/auth-flow.md
Modes: analyzer, architect, implementer

--- Analyzer Perspective (Conflicts) ---
- Tension between security and usability in token refresh
- Trade-off: session duration vs re-auth frequency

--- Architect Perspective (Restructure) ---
- Suggested: Extract token service from handler
- Benefit: Cleaner separation of concerns

--- Implementer Perspective (Implement) ---
- Implementation path: 3 stages
- Estimated complexity: Medium

Verdict: Approved

/ro gate output (pass)

[QUALITY GATE: Stage 2]
Status: ✓ PASSED

Checks:
- ✓ Tests pass (exit 0)
- ✓ Coverage maintained (delta: -1.2%)
- ✓ No critical findings
- ✓ Documentation updated

Proceed to Stage 3.

/ro gate output (block)

[QUALITY GATE: Stage 2]
Status: ✗ BLOCKED

Checks:
- ✓ Tests pass
- ✗ Coverage dropped (delta: -8.3%, threshold: 5%)
- ✓ No critical findings
- ✗ Documentation not updated

Action required before proceeding:
1. Add tests to restore coverage
2. Update docs/handlers/README.md

Example: API Design Review

/ro cognitive api/openapi.yaml --modes analyzer,architect
[COGNITIVE REVIEW INITIATED]
Target: api/openapi.yaml
Modes: analyzer, architect

--- Analyzer Perspective (Conflicts) ---
- Tension: Versioning strategy (URL vs header) inconsistent across endpoints
- Trade-off: Pagination style (cursor vs offset) mixed usage

--- Architect Perspective (Restructure) ---
- Suggested: Standardize on cursor pagination for large collections
- Benefit: Consistent client SDK, better performance at scale

Verdict: Approved with conditions

Example: Performance Review

/ro twin src/handlers/search.go --technical-only
[MULTI-PERSPECTIVE REVIEW INITIATED]
Target: src/handlers/search.go
Perspectives: technical

--- Technical Perspective Findings ---
Severity: important
- I-1: N+1 query pattern on line 78 (database calls in loop)
- I-2: Missing index on search_terms table

Severity: minor
- M-1: Consider caching frequent searches (>100 req/min)

Verdict: Approved with conditions

Integration

  • Layer: Review
  • Depends on: failure-memory (for context), context-verifier (for file verification)
  • Used by: governance (for constraint reviews)

Failure Modes

ConditionBehavior
Invalid sub-commandList available sub-commands
Target not foundError: "Target not found: {path}"
Agent spawn failedRetry once, then report failure
Gate check failedBlock with specific remediation steps

Next Steps

After invoking this skill:

ConditionAction
Review completeWrite findings to docs/reviews/
Gate passedProceed to next stage
Gate blockedAddress findings, re-run gate
Critical findingsCreate observation via /fm record

Workspace Files

This skill reads/writes:

docs/reviews/
├── [date]-[topic]-twin-technical.md
├── [date]-[topic]-twin-creative.md
├── [date]-[topic]-cognitive.md
└── [date]-[topic]-gate-results.md

Security Considerations

What this skill accesses:

  • Configuration files in .openclaw/review-orchestrator.yaml and .claude/review-orchestrator.yaml
  • Target files specified by user for review (read-only)
  • Its own output directory docs/reviews/

What this skill does NOT access:

  • Files outside declared workspace paths
  • System environment variables
  • Network resources or external APIs
  • Other tools' configuration

What this skill does NOT do:

  • Invoke AI models directly (instruction-only skill)
  • Call external services (Codex, Gemini, or any third-party API)
  • Send data to external services
  • Modify files outside its workspace (only writes to docs/reviews/)
  • Execute arbitrary code

Cognitive modes clarification: Mode names like "analyzer", "architect", and "implementer" describe review perspectives (analytical approaches), NOT external AI services. The skill provides prompts and structure; your agent executes the review using its configured model.

Configuration files: The config files (.openclaw/review-orchestrator.yaml and .claude/review-orchestrator.yaml) contain only local behavior settings (cognitive mode definitions, quality gate thresholds). They do NOT contain API keys, tokens, or external service endpoints by design.

Dependency clarification: References to failure-memory and context-verifier are skill-level dependencies installed via openclaw install. These are separate instruction-only skills with their own declared permissions — this skill does not grant them additional access or inherit their permissions.

Provenance note: This skill is developed by Live Neon (https://github.com/live-neon/skills) and published to ClawHub under the leegitw account. Both refer to the same maintainer.

Acceptance Criteria

  • [ ] /ro select recommends appropriate review type based on context and risk
  • [ ] /ro twin (or /ro multi) spawns both technical and creative perspectives
  • [ ] /ro twin aggregates findings from both perspectives
  • [ ] /ro cognitive spawns configured cognitive modes (default: analyzer, architect, implementer)
  • [ ] /ro cognitive presents different perspectives clearly
  • [ ] /ro gate checks all configured quality criteria
  • [ ] /ro gate blocks on critical failures
  • [ ] /ro gate provides clear remediation guidance
  • [ ] Review findings written to workspace files
  • [ ] Configuration loaded from .openclaw/ or .claude/ paths

*Consolidated from 5 skills as part of agentic skills consolidation (2026-02-15).*

平台分布

OpenClaw

85.1%
按下载量换算3,606

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install review-orchestrator 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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