Skill: athola/nm-pensive-unified-review (version 1.0.2)

--- name: unified-review description: | Orchestrate multiple review types into a single multi-domain review with integrated reporting version: 1.9.5 triggers: - review - orchestration - code-quality - analysis - multi-domain metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/pensive", "emoji": "\ud83e\udd9e", "requires": {"config": ["night-market.pensive:shared", "night-market.imbue:proof-of-work", "night-market.imbue:structured-output"]}}} source: claude-night-market source_plugin: pensive --- > **Night Market Skill** — ported from [claude-night-market/pensive](https://github.com/athola/claude-night-market/tree/master/plugins/pensive). For the full experience with agents, hooks, and commands, install the Claude Code plugin. ## Table of Contents - [Quick Start](#quick-start) - [When to Use](#when-to-use) - [Review Skill Selection Matrix](#review-skill-selection-matrix) - [Workflow](#workflow) - [1. Analyze Repository Context](#1-analyze-repository-context) - [2. Select Review Skills](#2-select-review-skills) - [3. Execute Reviews](#3-execute-reviews) - [4. Integrate Findings](#4-integrate-findings) - [Review Modes](#review-modes) - [Auto-Detect (default)](#auto-detect-(default)) - [Focused Mode](#focused-mode) - [Full Review Mode](#full-review-mode) - [Quality Gates](#quality-gates) - [Deliverables](#deliverables) - [Executive Summary](#executive-summary) - [Domain-Specific Reports](#domain-specific-reports) - [Integrated Action Plan](#integrated-action-plan) - [Modular Architecture](#modular-architecture) - [Exit Criteria](#exit-criteria) # Unified Review Orchestration Intelligently selects and executes appropriate review skills based on codebase analysis and context. ## Quick Start ```bash # 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. ## When To Use - Starting a full code review - Reviewing changes across multiple domains - Need intelligent selection of review skills - Want integrated reporting from multiple review types - Before merging major feature branches ## When NOT To Use - Specific review type known - use bug-review - Test-review - Architecture-only focus - use architecture-review - Specific review type known - use bug-review ## Review Skill Selection Matrix | 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 | ## Workflow ### 1. Analyze Repository Context - Detect primary languages from extensions and manifests - Analyze git status and diffs for change scope - Identify project structure (monorepo, microservices, library) - Detect build systems, testing frameworks, documentation ### 2. Select Review Skills ```python # 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. ### 3. Execute Reviews 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)` | **Rules:** - Never use skill names as agent types (e.g., `pensive:math-review` is NOT an agent) - When `pensive:code-reviewer` covers multiple domains, dispatch once with combined scope - For skills without dedicated agents, use `general-purpose` and instruct it to invoke the Skill tool - Maintain consistent evidence logging across all agents - Track progress via TodoWrite ### 4. Integrate Findings - Consolidate findings across domains - Identify cross-domain patterns - Prioritize by impact and effort - Generate unified action plan **Deferred 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: ```bash 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. ## Review Modes ### Auto-Detect (default) Automatically selects skills based on codebase analysis. ### Focused Mode 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 only ### Full Review Mode Run all applicable review skills: - `/full-review all` → Execute all detected skills ## Quality Gates Each review must: 1. Establish proper context 2. Execute all selected skills successfully 3. Document findings with evidence 4. Prioritize recommendations by impact 5. Create action plan with owners ## Deliverables ### Executive Summary - Overall codebase health assessment - Critical issues requiring immediate attention - Review frequency recommendations ### Domain-Specific Reports - API surface analysis and consistency - Architecture alignment with ADRs - Test coverage gaps and improvements - Bug analysis and security findings - Performance and maintainability recommendations ### Integrated Action Plan - Prioritized remediation tasks - Cross-domain dependencies - Assigned owners and target dates - Follow-up review schedule ## Modular Architecture All review skills use a hub-and-spoke architecture with progressive loading: - **`pensive:shared`**: Common workflow, output templates, quality checklists - **Each skill has `modules/`**: Domain-specific details loaded on demand - **Cross-plugin deps**: `imbue:proof-of-work`, `imbue:diff-analysis/modules/risk-assessment-framework` This reduces token usage by 50-70% for focused reviews while maintaining full capabilities. ## Exit Criteria - All selected review skills executed - Findings consolidated and prioritized - Action plan created with ownership - Evidence logged per structured output format ## Supporting Modules - [Review workflow core](modules/review-workflow-core.md) - standard 5-step workflow pattern for all pensive reviews - [Output format templates](modules/output-format-templates.md) - finding entry, severity, action item templates - [Quality checklist patterns](modules/quality-checklist-patterns.md) - pre-review, analysis, evidence, deliverable checklists ## Troubleshooting ### Common Issues 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.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)