菜单
Orchestrates multi-domain review (code, arch, tests, security) in a single pass. Use when thorough pre-release review is needed.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/athola/claude-night-market --skill unified-review命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
基于 SOC 职业分类
| name | unified-review |
| description | Orchestrates multi-domain review (code, arch, tests, security) in a single pass. Use when thorough pre-release review is needed. |
| alwaysApply | false |
| category | orchestration |
| tags | ["review","orchestration","code-quality","analysis","multi-domain"] |
| tools | [] |
| usage_patterns | ["auto-detect-review","full-review","focused-review"] |
| complexity | intermediate |
| model_hint | standard |
| estimated_tokens | 400 |
| progressive_loading | true |
| dependencies | ["imbue:proof-of-work","imbue:structured-output"] |
| orchestrates | ["pensive:rust-review","pensive:api-review","pensive:architecture-review","pensive:bug-review","pensive:test-review","pensive:makefile-review","pensive:math-review","imbue:justify"] |
Intelligently selects and executes appropriate review skills based on codebase analysis and context.
# Auto-detect and run appropriate reviews
/full-review
# Focus on specific areas
/full-review api # API surface review
/full-review architecture # Architecture review
/full-review bugs # Bug hunting
/full-review tests # Test suite review
/full-review all # Run all applicable skills
Verification: Run pytest -v to verify tests pass.
| Codebase Pattern | Review Skills | Triggers |
|---|---|---|
Rust files (*.rs, Cargo.toml) | rust-review, bug-review, api-review | Rust project detected |
API changes (openapi.yaml, routes/) | api-review, architecture-review | Public API surfaces |
Test files (test_*.py, *_test.go) | test-review, bug-review | Test infrastructure |
| Makefile/build system | makefile-review, architecture-review | Build complexity |
| Mathematical algorithms | math-review, bug-review | Numerical computation |
| Architecture docs/ADRs | architecture-review, api-review | System design |
| General code quality | bug-review, test-review | Default review |
| Post-implementation audit | imbue:justify | High add/delete ratio, test changes, new abstractions |
# Detection logic
if has_rust_files():
schedule_skill("rust-review")
if has_api_changes():
schedule_skill("api-review")
if has_test_files():
schedule_skill("test-review")
if has_makefiles():
schedule_skill("makefile-review")
if has_math_code():
schedule_skill("math-review")
if has_architecture_changes():
schedule_skill("architecture-review")
# Default
schedule_skill("bug-review")
Verification: Run pytest -v to verify tests pass.
Dispatch selected skills concurrently via the Agent tool. Use this mapping to resolve skill names to agent types:
| Skill Name | Agent Type | Notes |
|---|---|---|
| bug-review | pensive:code-reviewer | Covers bugs, API, tests |
| api-review | pensive:code-reviewer | Same agent, API focus |
| test-review | pensive:code-reviewer | Same agent, test focus |
| architecture-review | pensive:architecture-reviewer | ADR compliance |
| rust-review | pensive:rust-auditor | Rust-specific |
| code-refinement | pensive:code-refiner | Duplication, quality |
| math-review | general-purpose | Prompt: invoke Skill(pensive:math-review) |
| makefile-review | general-purpose | Prompt: invoke Skill(pensive:makefile-review) |
| shell-review | general-purpose | Prompt: invoke Skill(pensive:shell-review) |
Sub-agent isolation (required):
Dispatch ALL selected agents in a SINGLE parallel Agent tool call. Do not read or process any agent's output until ALL agents have returned their results. Reading the first result before the others are in anchors synthesis toward that perspective: each subsequent result gets evaluated against the first rather than independently. Collect all results, then synthesize once.
Rules:
pensive:math-review is NOT an agent)pensive:code-reviewer covers multiple domains, dispatch once with combined scopegeneral-purpose and instruct it to invoke the Skill toolDeferred capture for backlog findings: Findings that are triaged to the backlog (out-of-scope for the current review or deferred by the team) should be preserved so they are not lost between review cycles. For each finding assigned to the backlog, run:
python3 scripts/deferred_capture.py \
--title "<finding title>" \
--source review \
--context "Review dimension: <dimension>. <finding description>"
The <dimension> value should match the review skill that
surfaced the finding (e.g. bug-review, api-review,
architecture-review).
This runs automatically after the action plan is finalised,
without prompting the user.
Automatically selects skills based on codebase analysis.
Run specific review domains:
/full-review api → api-review only/full-review architecture → architecture-review only/full-review bugs → bug-review only/full-review tests → test-review onlyRun all applicable review skills:
/full-review all → Execute all detected skillsEach review must:
All review skills use a hub-and-spoke architecture with progressive loading:
modules/: Domain-specific details loaded on demandimbue:proof-of-work, imbue:diff-analysis/modules/risk-assessment-frameworkThis reduces token usage by 50-70% for focused reviews while maintaining full capabilities.
If the auto-detection fails to identify the correct review skills, explicitly specify the mode (e.g., /full-review rust instead of just /full-review). If integration fails, check that TodoWrite logs are accessible and that evidence files were correctly written by the individual skills.
Turn hunches into accepted results: worthiness score, evidence bar, research-to-rules. Use when vetting ideas. Not for QA; use night-market-validation-and-qa.
Generates and self-executes a diff-derived test plan for a PR. Use when validating PR changes before merge. Do not use for code review; use sanctum:pr-review.
Curate the web-capture index. Use when the capture backlog grows, captures sit unprocessed at seedling/pending, or to surface stored research during work.