refine
SolidTransform a brief or prompt into a structured, production-ready prompt via prompt-optimizer. File or text mode.
Install
Quality Score: 86/100
Skill Content
Details
- Author
- automagik-dev
- Repository
- automagik-dev/genie
- Created
- 10 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
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refine-prompt
Transforms vague or rough prompts into precise, structured AI instructions. Use when asked to "refine prompt", "improve prompt", "make this prompt better", "promptify", "optimize prompt", "rewrite prompt", "enhance prompt", or "sharpen instructions".
ia-refine-prompt
Transforms vague prompts into precise, structured AI instructions. Use when asked to refine, improve, or sharpen a prompt, do prompt engineering, write a system prompt, or make AI instructions more effective.
prompt-optimizer
Rigorous mode prompt optimizer — audits a polished prompt, decides output architecture (single-turn vs. chained multi-stage), and rewrites it to elicit state-of-the-art output from Claude. Triages every input into OUT OF PURVIEW / BORDERLINE / IN PURVIEW; rigorous optimization (architecture decision, 9-dim diagnostic, archetype detection, capability activation) applies ONLY to IN PURVIEW. When chain signals fire, produces a chain deliverable (README + Project orchestrator + per-stage prompts) instead of a single-turn prompt. Simple prompts return substantially unchanged with a triage note. Use when the user asks to optimize, audit, score, diagnose, sharpen, or level up a prompt; trigger phrases include "optimize this prompt", "PO this", "run this through the optimizer", "sharpen this prompt". For messy dictated or flow-state input, a separate flow-mode counterpart exists. Do NOT trigger when the user wants the prompt EXECUTED rather than optimized.
prompt-optimizer
Prompt analysis and optimization workflow for turning rough requests into clearer task prompts. Use when the user asks to improve or rewrite a prompt.
prompt-engineer
Optimize system prompts for Claude Code agents using proven prompt engineering patterns. Use when users request prompt improvement, optimization, or refinement for agent workflows, tool instructions, or system behaviors.