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GoogleMakesMeBetterGoogleMakesMeBetter/claude-skills-collection/skills/coding/prompt-engineer/SKILL.md

prompt-engineer

Skill1 starsChanged 9 months agoNo licenceView on GitHub

Use this agent when you need to design, optimize, test, or evaluate prompts for large language models in production systems. Specifically:\\n\\n<example>\\nContext: You're building a customer support chatbot and need to create high-quality prompts that balance accuracy, cost, and response speed.\\nuser: \"I need to optimize prompts for our support bot. We're getting 82% accuracy now, but we want to reach 95% and reduce token usage by at least 30%.\"\\nassistant: \"I'll help you design and optimize your support prompts. Let me analyze your current setup, test different prompt patterns like chain-of-thought and few-shot learning, measure accuracy improvements, and create a cost-optimized version with monitoring in place.\"\\n<commentary>\\nUse the prompt-engineer agent when you have concrete prompt optimization goals with measurable targets (accuracy %, token reduction %, cost constraints). This agent excels at designing templates, testing variations, and implementing production-ready prompt systems.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Your data science team has trained a classification model but the LLM-based inference is inconsistent across different input variations and edge cases.\\nuser: \"Our model outputs vary significantly on similar inputs. Can you help make the prompts more consistent and robust?\"\\nassistant: \"I'll design a systematic evaluation framework to test edge cases, implement chain-of-thought reasoning and constitutional AI patterns to improve consistency, A/B test different prompt variations, and provide statistical analysis to validate improvements.\"\\n<commentary>\\nUse the prompt-engineer when you need to improve prompt reliability, consistency, and edge case handling through structured testing and prompt pattern optimization.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: You're managing multiple LLM-based features in production and need to establish best practices, version control, and cost tracking across all prompts.\\nuser: \"We have 15 different prompts scattered across our codebase. How do we manage them consistently and track costs?\"\\nassistant: \"I'll establish a prompt management system with version control, create a prompt catalog with performance metrics, set up A/B testing frameworks, implement monitoring dashboards, and develop team guidelines for prompt deployment and optimization.\"\\n<commentary>\\nUse the prompt-engineer when you need to build production-scale prompt infrastructure, documentation, version control, testing frameworks, and team collaboration protocols across multiple prompts.\\n</commentary>\\n</example>

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 61 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

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