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/majiayu000/claude-skill-registry --skill prompt-optimization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。
LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据,按主题分组汇总"我都做了什么",并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| name | prompt-optimization |
| description | Analyze and improve existing prompts for better performance |
| allowed-tools | Read, Write, Edit |
Skill for analyzing and improving existing prompts.
1. ANALYZE current prompt
↓
2. IDENTIFY issues
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3. APPLY corrections
↓
4. VALIDATE improvement
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5. DOCUMENT changes
Before:
Write a good summary.
After:
Write a 100-150 word summary that:
1. Captures the main idea in the first sentence
2. Includes 2-3 supporting key points
3. Uses accessible language (high school level)
4. Avoids technical jargon
Before:
Analyze this code.
After:
Analyze this Python code focusing on:
- Performance (algorithmic complexity)
- Readability (PEP 8 conventions)
- Security (OWASP vulnerabilities)
Context: Code for production REST API, 10k requests/day.
Before:
Give me recommendations.
After:
Provide 3-5 recommendations in this format:
## Recommendation [N]: [Short title]
**Impact:** [High/Medium/Low]
**Effort:** [High/Medium/Low]
**Action:** [1-2 sentence description]
Before:
Translate this text to French.
After:
Translate this text to French.
IF the text is already in French:
→ Indicate "The text is already in French" and suggest style improvements.
IF the text contains technical jargon:
→ Keep technical terms in English with translation in parentheses.
IF the text is too long (>1000 words):
→ Ask for confirmation before proceeding.
Before:
Don't make up information.
After:
CRITICAL - ZERO TOLERANCE: NEVER make up information.
IF uncertain → Explicitly say "I'm not sure about..."
IF no data → Say "I don't have this information"
# Addition
Before answering, think step by step:
1. What exactly is being asked?
2. What information do I have?
3. What is the best approach?
4. Are there pitfalls to avoid?
# Addition
## Examples
### Good example
Input: [...]
Output: [Expected output]
### Bad example (to avoid)
Input: [...]
Incorrect output: [What we don't want]
Why incorrect: [Explanation]
# Addition
## Forbidden (STRICT)
- [Forbidden behavior 1]
- [Forbidden behavior 2]
## Required (ALWAYS)
- [Required behavior 1]
- [Required behavior 2]
# Optimization of [Prompt Name]
## Before/After Score
| Criterion | Before | After |
|-----------|--------|-------|
| Clarity | X/10 | Y/10 |
| Structure | X/10 | Y/10 |
| Completeness | X/10 | Y/10 |
| Guardrails | X/10 | Y/10 |
| **Total** | **X/40** | **Y/40** |
## Identified Issues
1. [Issue 1]
2. [Issue 2]
## Applied Changes
| Before | After | Reason |
|--------|-------|--------|
| [...] | [...] | [...] |
## Optimized Prompt
---
[THE COMPLETE PROMPT]
---
## Recommended Tests
- [ ] Standard case test
- [ ] Edge case test 1
- [ ] Edge case test 2