一键导入
requesting-code-review
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
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。
菜单
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
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。
基于 SOC 职业分类
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Systematically identify what's missing, unknown, or needs investigation before making changes or decisions. Use proactively when proposing features, implementing changes, or making technical decisions to ensure all critical areas are covered. This skill catches overlooked dependencies, edge cases, and integration points before they become problems. Examples: - "Implement user authentication" → trigger gap analysis (what's the current auth system?) - "Add caching to API" → trigger gap analysis (what caching infrastructure exists?) - "Migrate to TypeScript" → trigger gap analysis (what's the build pipeline?) - "Refactor this module" → trigger gap analysis (what depends on this module?) - "Add new API endpoint" → trigger gap analysis (what endpoints exist, what patterns?)
Detect ambiguous or underspecified research requests and guide through structured clarification questions before executing any research. Use proactively when user requests are vague, lack specificity, missing context, or have unclear goals. This skill prevents wasted research by ensuring intent is crystal clear before any web searches, file reads, or data gathering. Examples: - "Research the codebase" → ❌ Too vague, trigger clarification - "Why is this slow?" → ❌ Missing context (what is "this"?), trigger clarification - "Add a feature" → ❌ Not research, this is implementation - "Investigate authentication flow" → ❌ What specifically about it? Trigger clarification - "Compare React and Vue" → ✅ Specific enough, but still validate dimensions
Evaluate requests, proposals, or decisions from multiple dimensions (technical, business, UX, security, performance, maintainability, etc.) to ensure holistic understanding before proceeding. Use proactively when making technical decisions, choosing solutions, or proposing changes. This skill prevents single-minded thinking and uncovers trade-offs, risks, and opportunities across all relevant aspects. Examples: - "Use Redis for caching" → assess multiple aspects (performance, cost, complexity, ops) - "Add AI to our app" → assess aspects (technical feasibility, user experience, data privacy) - "Refactor to microservices" → assess aspects (benefits, costs, migration complexity, team readiness) - "Implement authentication" → assess aspects (security, UX, integration effort, maintenance) - "Switch to React 19" → assess aspects (benefits, migration cost, breaking changes, learning curve)
Choose the right OpenCode primitive (Command, Skill, Tool, Prompt, CustomTool, Plugin hook) for a given task or workflow. Use proactively when deciding which OpenCode capability to use, or when trying to understand what's available. This skill maps research and development needs to appropriate OpenCode mechanisms, ensuring optimal use of the platform's capabilities. Examples: - "How do I search the codebase?" → select tool (read/grep) - "I need a reusable workflow for feature development" → select command - "How do I intercept file writes?" → select plugin hook - "What primitive should I use for systematic debugging?" → select skill - "I need a custom tool for X" → select CustomTool (if innate tools insufficient)
Create structured, executable research plans with clear phases, checkpoints, and validation criteria. Use proactively when research intent is clear but execution plan is missing. This skill transforms research goals into actionable workflows with defined deliverables, time estimates, and success metrics, ensuring research is systematic and produces useful outputs. Examples: - "Research how to add OAuth" (intent clear, need plan) → trigger workflow planner - "Investigate performance bottlenecks" (intent clear, need plan) → trigger workflow planner - "Analyze codebase architecture" (intent clear, need plan) → trigger workflow planner - "Find best practices for X" (intent clear, need plan) → trigger workflow planner - "Compare technology options" (intent clear, need plan) → trigger workflow planner
| name | requesting-code-review |
| description | Use when completing tasks, implementing major features, or before merging to verify work meets requirements |
Dispatch superpowers:code-reviewer subagent to catch issues before they cascade.
Core principle: Review early, review often.
Mandatory:
Optional but valuable:
1. Get git SHAs:
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main
HEAD_SHA=$(git rev-parse HEAD)
2. Dispatch code-reviewer subagent:
Use Task tool with superpowers:code-reviewer type, fill template at code-reviewer.md
Placeholders:
{WHAT_WAS_IMPLEMENTED} - What you just built{PLAN_OR_REQUIREMENTS} - What it should do{BASE_SHA} - Starting commit{HEAD_SHA} - Ending commit{DESCRIPTION} - Brief summary3. Act on feedback:
[Just completed Task 2: Add verification function]
You: Let me request code review before proceeding.
BASE_SHA=$(git log --oneline | grep "Task 1" | head -1 | awk '{print $1}')
HEAD_SHA=$(git rev-parse HEAD)
[Dispatch superpowers:code-reviewer subagent]
WHAT_WAS_IMPLEMENTED: Verification and repair functions for conversation index
PLAN_OR_REQUIREMENTS: Task 2 from docs/plans/deployment-plan.md
BASE_SHA: a7981ec
HEAD_SHA: 3df7661
DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types
[Subagent returns]:
Strengths: Clean architecture, real tests
Issues:
Important: Missing progress indicators
Minor: Magic number (100) for reporting interval
Assessment: Ready to proceed
You: [Fix progress indicators]
[Continue to Task 3]
Subagent-Driven Development:
Executing Plans:
Ad-Hoc Development:
Never:
If reviewer wrong:
See template at: requesting-code-review/code-reviewer.md