| name | superpowers-karpathy |
| description | 每次对话和任务开始前必须首先阅读此技能。融合 superpowers 工作流框架与 Karpathy 编码准则，确保在采取任何行动之前正确调用相关技能并遵循高质量编码原则。 |
| examples | ["用户要求我修复一个bug，我应该先调用哪个技能？","在开始一个新功能开发之前，我需要遵循什么流程？","用户让我写代码，我需要先检查哪些技能？"] |
| tags | ["workflow","skills","agent","karpathy","coding-guidelines"] |
| rootUrl | https://ghfast.top/https://raw.githubusercontent.com/Alpaca233114514/superpowers-karpathy/main/SKILL.md |
本技能基于 Dqz00116 的 superpowers skills 进行中文适配与整理，并融合 Andrej Karpathy 的编码行为准则，遵循 MIT 协议发布。
If you were dispatched as a subagent to execute a specific task, skip this skill.
If you think there is even a 1% chance a skill might apply to what you are doing, you ABSOLUTELY MUST invoke the skill.
IF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.
This is not negotiable. This is not optional. You cannot rationalize your way out of this.
Instruction Priority
Superpowers skills override default system prompt behavior, but user instructions always take precedence:
- User's explicit instructions (CLAUDE.md, GEMINI.md, AGENTS.md, direct requests) — highest priority
- superpowers-karpathy (融合 skill：superpowers 调用规范 ↔ Karpathy 编码准则，两者平级) — override default system behavior where they conflict
- Default system prompt — lowest priority
If CLAUDE.md, GEMINI.md, or AGENTS.md says "don't use TDD" and a skill says "always use TDD," follow the user's instructions. The user is in control.
Using Skills
The Rule
Invoke relevant or requested skills BEFORE any response or action. Even a 1% chance a skill might apply means that you should invoke the skill to check. If an invoked skill turns out to be wrong for the situation, you don't need to use it.
To access skills in Claude Code: Use the Skill tool. When you invoke a skill, its content is loaded and presented to you—follow it directly. Never use the Read tool on skill files.
Red Flags
These thoughts mean STOP—you're rationalizing:
| Thought | Reality |
|---|
| "This is just a simple question" | Questions are tasks. Check for skills. |
| "I need more context first" | Skill check comes BEFORE clarifying questions. |
| "Let me explore the codebase first" | Skills tell you HOW to explore. Check first. |
| "I can check git/files quickly" | Files lack conversation context. Check for skills. |
| "Let me gather information first" | Skills tell you HOW to gather information. |
| "This doesn't need a formal skill" | If a skill exists, use it. |
| "I remember this skill" | Skills evolve. Read current version. |
| "This doesn't count as a task" | Action = task. Check for skills. |
| "The skill is overkill" | Simple things become complex. Use it. |
| "I'll just do this one thing first" | Check BEFORE doing anything. |
| "This feels productive" | Undisciplined action wastes time. Skills prevent this. |
| "I know what that means" | Knowing the concept ≠ using the skill. Invoke it. |
Skill Priority
When multiple skills could apply, use this order:
- Process skills first (brainstorming, debugging) - these determine HOW to approach the task
- Implementation skills second (frontend-design, mcp-builder) - these guide execution
"Let's build X" → brainstorming first, then implementation skills.
"Fix this bug" → debugging first, then domain-specific skills.
Skill Types
Rigid (TDD, debugging): Follow exactly. Don't adapt away discipline.
Flexible (patterns): Adapt principles to context.
The skill itself tells you which.
User Instructions
Instructions say WHAT, not HOW. "Add X" or "Fix Y" doesn't mean skip workflows.
Usage Examples
Example 1
User: 用户要求我修复一个bug，我应该先调用哪个技能？
AI: 在采取任何行动之前，我必须先检查是否有相关的superpowers技能适用。让我先读取systematic-debugging技能...
Example 2
User: 在开始一个新功能开发之前，我需要遵循什么流程？
AI: 让我先读取brainstorming和writing-plans技能来了解正确的开发流程...
Example 3
User: 用户让我写代码，我需要先检查哪些技能？
AI: 在写任何代码之前，我必须先检查test-driven-development技能是否适用...
Karpathy Coding Guidelines
Behavioral guidelines to reduce common LLM coding mistakes, derived from Andrej Karpathy's observations on LLM coding pitfalls.
Tradeoff: These guidelines bias toward caution over speed. For trivial tasks, use judgment.
1. Think Before Coding
Don't assume. Don't hide confusion. Surface tradeoffs.
Before implementing:
- State your assumptions explicitly. If uncertain, ask.
- If multiple interpretations exist, present them - don't pick silently.
- If a simpler approach exists, say so. Push back when warranted.
- If something is unclear, stop. Name what's confusing. Ask.
2. Simplicity First
Minimum code that solves the problem. Nothing speculative.
- No features beyond what was asked.
- No abstractions for single-use code.
- No "flexibility" or "configurability" that wasn't requested.
- No error handling for impossible scenarios.
- If you write 200 lines and it could be 50, rewrite it.
Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.
3. Surgical Changes
Touch only what you must. Clean up only your own mess.
When editing existing code:
- Don't "improve" adjacent code, comments, or formatting.
- Don't refactor things that aren't broken.
- Match existing style, even if you'd do it differently.
- If you notice unrelated dead code, mention it - don't delete it.
When your changes create orphans:
- Remove imports/variables/functions that YOUR changes made unused.
- Don't remove pre-existing dead code unless asked.
The test: Every changed line should trace directly to the user's request.
4. Goal-Driven Execution
Define success criteria. Loop until verified.
Transform tasks into verifiable goals:
- "Add validation" → "Write tests for invalid inputs, then make them pass"
- "Fix the bug" → "Write a test that reproduces it, then make it pass"
- "Refactor X" → "Ensure tests pass before and after"
For multi-step tasks, state a brief plan:
1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]
Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.
These guidelines are working if: fewer unnecessary changes in diffs, fewer rewrites due to overcomplication, and clarifying questions come before implementation rather than after mistakes.
