prompt-engineering
From the author
Use when one prompt must give the same right answer across reruns, models, and pasted-in hostile input: forcing a fixed schema, picking the few-shot set, ordering the prompt blocks, or the inline cases you run while tuning. NOT the agent loop, tools, or retrieval (that is `building-agents`), NOT a standing CI eval harness (that is `agent-eval`).
Install
npx skills add ericrisco/rsc-harness --skill prompt-engineering -a claude-code
Installs to .claude/skills/prompt-engineering/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Why 79
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Similar skills
Closest to this one by what they do and when they are used.
- prompt-engineering-patternswshobson/agentsThis skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot prompting", or wants to apply advanced prompt engineering patterns for production LLM applications.Design★ 41.6K
- prompt-engineerJeffallan/claude-skillsWrites, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot learning, creating system prompts with personas and guardrails, building JSON/function-calling schemas, or developing prompt evaluation frameworks to measure and improve model performance.Testing★ 12K
- prompt-engineer-toolkitborghei/Claude-SkillsPrompt engineering frameworks for building, testing, versioning, and evaluating prompts: chain-of-thought, few-shot, regression testing, and rubrics. Use when designing production prompts, running A/B tests, or building prompt libraries.Testing★ 971
- prompt-architectckelsoe/prompt-architectAnalyzes and improves prompts using 31 frameworks across 7 intent categories. Use when a user wants to improve, rewrite, structure, or engineer a prompt — including requests like "help me write a better prompt", "improve this prompt", "what framework should I use", "make this prompt more effective", or any prompt engineering task. Recommends the right framework based on intent (create, transform, reason, critique, recover, clarify, agentic), asks targeted questions, and delivers a structured, high-quality result.Planning★ 322
- roast-meericrisco/rsc-harnessUse when someone wants an honest, comedic audit of their own prompting — reads their past agent transcripts, scores prompt quality and compute efficiency, names their worst habits, builds a model-selection cheat sheet. NOT reviewing code an agent produced (that is `code-review`), NOT prompting technique in general (that is `prompt-engineering`).Engineering★ 255
- prompt-testingnaodeng/awesome-qa-skillsUse this skill when you need to test prompt behavior, regression risk, and output boundaries across versions; triggers include prompt testing and prompt-regression.Testing★ 279
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