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JaimeJunr
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prompt-optimize

Analyze draft prompts and generate optimized versions without executing the task.

2|Updated Apr 11, 2026
Search Tags:#workflow#optimization#Claude#analysis#LLM#prompt-engineering#prompt
One-click install
npx skills add https://github.com/JaimeJunr/context-mode --skill prompt-optimize-jaimejunr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-optimize
Source: https://github.com/JaimeJunr/context-mode/tree/main/.claude/skills/prompt-optimize
Command: npx skills add https://github.com/JaimeJunr/context-mode --skill prompt-optimize-jaimejunr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Este Skill analisa um prompt em rascunho e gera uma versão otimizada, sem executar a tarefa. Ele foca em melhorar clareza, foco e instrutibilidade para maximizar o resultado ao ser utilizado por modelos de linguagem.

Core Features & Use Cases

  • Pipeline de seis fases: Detecção de projeto, detecção de intenção, avaliação de escopo, mapeamento de componentes, detecção de contexto faltante e diretrizes de workflow/modelo.
  • Saída determinística: Retorna diagnóstico estruturado e um prompt otimizado pronto para uso.
  • Não executa a tarefa: Fornece apenas análise e recomendações, sem acionar o modelo.

Quick Start

Provide a draft prompt to the prompt-optimize skill and request an optimized version.

Frequently Asked Questions about prompt-optimize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize a draft prompt for an LLM without executing the task?▼

A prompt optimization pipeline analyzes your draft text through a six-phase process including project detection, intent detection, and scope assessment to generate a refined, deterministic prompt version without executing the original task.

What is prompt analysis and how does component mapping improve LLM inputs?▼

Prompt analysis uses component mapping and missing context detection to evaluate draft instructions, identifying structural weaknesses to ensure the optimized output provides clear focus and instructibility for language models.

Can I get structured diagnostics for prompt engineering before running a workflow?▼

Yes, you can get structured diagnostics for prompt engineering by submitting a draft prompt to receive deterministic output, which includes an analysis of missing context and specific workflow or model guidance without triggering the task.

Does prompt optimization work with Claude models for workflow guidance?▼

Yes, prompt optimization provides specific workflow and model guidance tailored for LLMs like Claude, applying scope assessment and intent detection to refine instructions before execution.

What are the limitations of using a prompt optimization pipeline?▼

The primary limitation of a prompt optimization pipeline is that it strictly analyzes and refines text; it does not execute the target task, meaning users must run the generated optimized prompt separately in their actual workflow.

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