Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.
How to install senior-prompt-engineer?
hanamizuki/solopreneur/senior-prompt-engineer
$npx -y skills add hanamizuki/solopreneur --skill senior-prompt-engineerInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/hanamizuki/solopreneur" --skill "hanamizuki/solopreneur/senior-prompt-engineer"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/hanamizuki/solopreneur" that are relevant to the current task. Run `npx skills add "https://github.com/hanamizuki/solopreneur"` and select the relevant skills, then follow their instructions.
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