think-before-coding
Forces explicit reasoning before writing any code. Surfaces assumptions, manages confusion, and prevents hallucination by demanding clarity upfront.
适合你,如果常因思路不清而写出有问题的代码
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
~/.claude/skills/(项目级 .claude/skills/)~/.codex/skills/npx oh-my-skill add developersglobal/ai-agent-skills/think-before-codingcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- developersglobal/ai-agent-skills/think-before-codingnpx oh-my-skill verify developersglobal/ai-agent-skills/think-before-coding怎么用
技能原文 SKILL.md
Overview
AI agents default to writing code immediately — even when the request is ambiguous, the context is incomplete, or multiple valid interpretations exist. This skill forces a deliberate thinking phase before any implementation begins.
The result: fewer rewrites, fewer wrong-direction implementations, and fewer "I assumed X" surprises.
When to Use
Activate this skill before writing any code when:
- The request is ambiguous or underspecified
- Multiple valid implementations exist
- You are unsure about an existing system's constraints
- The task touches security, data integrity, or public APIs
- You feel the urge to "just start coding" to make progress
Process
Phase 1: Understand the Request
- Read the full request — Do not skim. Re-read once.
- Identify ambiguities — List every decision you would have to make silently:
- What counts as "success"?
- What are the inputs and expected outputs?
- What should NOT change?
- Are there existing patterns to follow?
- Surface assumptions — Write them out: "I am assuming X because Y."
- Check for contradictions — Does the request contradict itself or existing code?
Verify: Can you state the goal in one clear sentence? If not, ask before proceeding.
Phase 2: Clarify Before Acting
- If genuinely ambiguous, ask a focused clarifying question — not a list of 10 questions. Pick the one blocker.
- If multiple valid approaches exist, present 2–3 options with tradeoffs, then ask which to proceed with.
- If something seems wrong with the request, say so directly — don't silently work around it.
Verify: You have a clear, agreed-upon interpretation of the task.
Phase 3: State Your Plan
- Before writing code, state:
- What you will build
- What you will NOT touch
- What success looks like (your verification criteria)
- For multi-step tasks, write a brief plan: ```
- [Step] → verify: [check]
- [Step] → verify: [check]
- [Step] → verify: [check] ```
Verify: The plan is agreed upon, or you have received approval to proceed.
Phase 4: Code
- Now write the code — following the plan exactly.
Common Rationalizations (and Rebuttals)
| Excuse | Rebuttal | |--------|----------| | "I'll figure it out as I go" | Unknown unknowns compound. 5 minutes of thinking saves 50 minutes of rewriting. | | "The request is clear enough" | If you can't state the goal in one sentence, it's not clear enough. | | "Asking questions slows things down" | Wrong direction is infinitely slower than a 30-second clarifying question. | | "I'll handle edge cases later" | Edge cases not considered upfront become bugs found in production. | | "I can always refactor" | You almost never will. Design now. |
Red Flags
- You're already writing code and you haven't stated what success looks like
- You made a silent assumption about what the user wants
- You chose between two approaches without mentioning the tradeoff
- You're solving a problem the user didn't ask about
- You're 100 lines in and realize you misunderstood the goal
Verification
Before leaving this phase, confirm:
- [ ] The goal is stated in one clear sentence
- [ ] All major assumptions are explicitly named
- [ ] Ambiguities are resolved (or flagged for the user)
- [ ] A brief plan exists with verification criteria per step
- [ ] You know what you will NOT touch
References
- Andrej Karpathy on LLM coding pitfalls
- [goal-driven-execution skill](../goal-driven-execution/SKILL.md)
- [idea-to-spec skill](../idea-to-spec/SKILL.md)