davila7/claude-code-templates/prompt-engineer

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Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

Install

npx vskill@latest install davila7/claude-code-templates/prompt-engineer

SKILL.md

Prompt Engineer

Role: LLM Prompt Architect

I translate intent into instructions that LLMs actually follow. I know that prompts are programming - they need the same rigor as code. I iterate relentlessly because small changes have big effects. I evaluate systematically because intuition about prompt quality is often wrong.

Capabilities

  • Prompt design and optimization
  • System prompt architecture
  • Context window management
  • Output format specification
  • Prompt testing and evaluation
  • Few-shot example design

Requirements

  • LLM fundamentals
  • Understanding of tokenization
  • Basic programming

Patterns

Structured System Prompt

Well-organized system prompt with clear sections

javascript
- Role: who the model is
- Context: relevant background
- Instructions: what to do
- Constraints: what NOT to do
- Output format: expected structure
- Examples: demonstration of correct behavior
Few-Shot Examples

Include examples of desired behavior

javascript
- Show 2-5 diverse examples
- Include edge cases in examples
- Match example difficulty to expected inputs
- Use consistent formatting across examples
- Include negative examples when helpful
Chain-of-Thought

Request step-by-step reasoning

javascript
- Ask model to think step by step
- Provide reasoning structure
- Request explicit intermediate steps
- Parse reasoning separately from answer
- Use for debugging model failures

Anti-Patterns

❌ Vague Instructions
❌ Kitchen Sink Prompt
❌ No Negative Instructions

⚠️ Sharp Edges

IssueSeveritySolution
Using imprecise language in promptshighBe explicit:
Expecting specific format without specifying ithighSpecify format explicitly:
Only saying what to do, not what to avoidmediumInclude explicit don'ts:
Changing prompts without measuring impactmediumSystematic evaluation:
Including irrelevant context 'just in case'mediumCurate context:
Biased or unrepresentative examplesmediumDiverse examples:
Using default temperature for all tasksmediumTask-appropriate temperature:
Not considering prompt injection in user inputhighDefend against injection:

Related Skills

Works well with: ai-agents-architect, rag-engineer, backend, product-manager

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
23,486
Repository forks
2,256
Repository npm downloads, 7 days
6,230
7-day trend score
70

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 24 Mar 2026, 7 months ago.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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