prompting
0
总安装量
20
周安装量
安装命令
npx skills add https://github.com/diskd-ai/prompting --skill prompting
Agent 安装分布
opencode
16
claude-code
16
gemini-cli
15
codex
14
cursor
11
Skill 文档
Prompt Engineering
Guide for crafting effective prompts for large language models (Claude, GPT, Gemini, Llama, etc.).
Workflow
- Clarify the goal: What task should the prompt accomplish?
- Choose techniques: Select from references/techniques.md
- Structure the prompt: Apply appropriate format
- Add constraints: Specify requirements and boundaries
- Test and refine: Iterate based on outputs
Writing a New Prompt
Start with this template:
[Context/Role - optional]
[Task - required]
[Constraints/Requirements - as needed]
[Output format - as needed]
[Examples - for complex tasks]
Minimal prompt (simple tasks):
Summarize this article in 3 bullet points.
Structured prompt (complex tasks):
You are a senior code reviewer.
Review this code for:
- Security vulnerabilities
- Performance issues
- Maintainability concerns
Format your response as:
## Summary
[1-2 sentences]
## Issues
- [severity]: [description]
## Recommendations
[prioritized list]
Improving an Existing Prompt
Diagnose issues:
| Problem | Solution |
|---|---|
| Output too vague | Add specific constraints or examples |
| Wrong format | Specify output structure explicitly |
| Missing details | Use chain-of-thought or decomposition |
| Inconsistent results | Add few-shot examples |
| Off-topic responses | Strengthen role/context framing |
Improvement checklist:
- Is the task clear and unambiguous?
- Are constraints specific (not “be concise” but “under 100 words”)?
- Does output format match intended use?
- Would examples clarify expectations?
Quick Reference: Techniques
| Technique | When to Use |
|---|---|
| Few-shot | Specific format/style needed |
| Chain-of-thought | Complex reasoning, math, analysis |
| Role prompting | Domain expertise, specific tone |
| Task decomposition | Multi-step workflows |
| Constraints | Precise requirements |
See references/techniques.md for detailed patterns and examples.
Quick Reference: Output Formats
| Format | When to Use |
|---|---|
| XML tags | Complex prompts, clear section boundaries |
| JSON | Programmatic parsing, structured data |
| Markdown | Human-readable reports, documentation |
See references/structured.md for format patterns.
System Prompts
For designing AI assistant behavior, see references/system-prompts.md.
Key sections:
- Identity and role definition
- Behavioral guidelines
- Constraints and boundaries
- Output format defaults