review-orchestrator
Get multiple perspectives on your work — coordinate reviews across cognitive modes
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/leegitw/review-orchestratorreview-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:
- Twin review — technical and creative perspectives for balance
- 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
| Command | CJK | Logic | Trigger |
|---|---|---|---|
/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
| Argument | Required | Description |
|---|---|---|
| context | Yes | Description of work to review |
| --risk | No | Risk level: low, medium, high (auto-detected if omitted) |
/ro twin
| Argument | Required | Description |
|---|---|---|
| target | Yes | File path(s) or topic to review |
| --technical-only | No | Skip creative perspective |
| --creative-only | No | Skip technical perspective |
/ro cognitive
Metadata
Not sure this is the right skill?
Describe what you want to build — we'll match you to the best skill from 16,000+ options.
Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-leegitw-review-orchestrator": {
"enabled": true,
"auto_update": true
}
}
}Tags
Related Skills
verify-before-done
Prevent premature completion claims, repeated same-pattern retries, and weak handoffs. Use this skill to improve verification, strategy switching, and blocked-task reporting without changing personality or tone.
evidence-gap-mapper
在报告、方案或演示稿中定位结论先行但证据不足的位置,并给出补证优先级。;use for evidence, gap-analysis, research workflows;do not use for 伪造数据支撑结论, 忽略高风险假设.
q-kdb-code-review
AI-powered code review for Q/kdb+ — catch bugs in the most terse language in finance
human_test
Call real humans to test your product (URL or app). Get structured usability feedback with screen recordings, NPS scores, and AI-aggregated findings.
astrai-code-review
AI-powered code review with intelligent model routing — saves 40%+ vs always using the most expensive model