AgentSkillsCN

prompting

撰写清晰、高效的LLM提示的技能。涵盖结构、具体性、角色设定、示例、输出格式规范及迭代优化。适用于Claude、GPT及其他语言模型的通用原则。

SKILL.md
--- frontmatter
name: prompting
description: >-
  Skill for writing clear, effective LLM prompts. Covers structure,
  specificity, role-setting, examples, output format specification,
  and iterative refinement. Model-agnostic principles that work
  across Claude, GPT, and other language models.

Prompting

Principles and techniques for writing clear, effective LLM prompts that produce consistent, high-quality output.

Core Principles

  1. •Be clear and specific — Treat the model as a skilled worker with zero context. Spell out the task, audience, purpose, and what success looks like. Replace vague quantifiers ("keep it short") with concrete ones ("2-3 sentences").
  2. •Say what TO do, not what NOT to do — Positive instructions ("respond in formal tone") outperform negative ones ("don't be casual").
  3. •Structure the prompt — Use sections, headers, or delimiters to separate role, instructions, context, examples, and output format.
  4. •Set a role — A specific persona improves accuracy, tone, and depth. Be precise: "You are a senior backend engineer reviewing a pull request" beats "You are a developer."
  5. •Specify the output format — Never assume defaults. Define: format (bullets, JSON, prose), length, tone, structure.
  6. •Provide examples — 3-5 diverse examples dramatically improve output quality. Examples should be relevant, varied, and clearly delimited.
  7. •Give context — Who is the audience, what is the purpose, where does this fit in a larger workflow.
  8. •Let it think — For complex tasks, instruct step-by-step reasoning. Don't suppress the thinking.
  9. •Permit uncertainty — Let the model say "I don't know" rather than fabricate answers.

Prompt Structure Template

code
# Role and Objective
[Who the model is and what it should accomplish]

## Instructions
[Numbered steps for the task]

## Context
[Background information, audience, purpose]

## Output Format
[Exact format, length, tone specifications]

## Examples (optional)
[3-5 input/output pairs wrapped in delimiters]

Formatting Rules

  • •Use markdown headers (##) to separate sections
  • •Use XML tags (<context>, <example>, <output>) when nesting is needed
  • •Use numbered lists for sequential steps
  • •Use bullet points for parallel items
  • •Keep the prompt scannable — a human should be able to skim and understand the structure

Common Mistakes to Avoid

  • •Vague instructions ("make it good") → be concrete about quality criteria
  • •Missing context → always state audience, purpose, constraints
  • •No output format → always specify format, length, tone
  • •Mixing instructions with data → use delimiters to separate
  • •Over-engineering → start simple, add complexity only when needed

Quality Checklist

Apply before outputting the final prompt:

  • • Has a clear role or persona
  • • Instructions use action verbs (Write, Classify, Summarize, Analyze)
  • • Output format is explicitly defined
  • • Audience and purpose are stated
  • • Examples are included if the task involves specific formatting
  • • No vague quantifiers remain
  • • No negative instructions where positive ones would work