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prompt-optimizer

Optimize prompts by mapping ECC commands, skills, agents, workflows, acceptance criteria, and scope boundaries.

2|Updated Apr 7, 2026
Search Tags:#prompt engineering#claude code#prompt optimization#task automation#coding workflow#ai prompting#ecc
One-click install
npx skills add https://github.com/Zenobia000/ai-brainstorming --skill prompt-optimizer-zenobia000
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/Zenobia000/ai-brainstorming/tree/main/.claude/custom-rule%26skill/skills/prompt-optimizer
Command: npx skills add https://github.com/Zenobia000/ai-brainstorming --skill prompt-optimizer-zenobia000

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill fixes vague, incomplete user prompts that fail to leverage the Claude Code ecosystem (ECC), leading to poor task execution, missed requirements, and wasted time reworking outputs.

Core Features & Use Cases

  • Intent & Gap Analysis: Automatically classifies task intent (coding, research, infrastructure, etc.) and identifies missing context like tech stack, acceptance criteria, and scope boundaries.
  • ECC Component Matching: Maps the task to the correct ECC commands, skills, and agents for the user's specific project and tech stack, ensuring optimal workflow alignment.
  • Structured Optimized Output: Returns a complete, copy-paste ready prompt with clear workflow steps, security requirements, verification steps, and explicit do-not-do boundaries.
  • Use Case: For example, if a user submits a vague prompt like "add a user login page", the skill will detect the project's Next.js + TypeScript stack, map it to /plan, /tdd, and /code-review commands, and output a fully specified prompt with form validation, security requirements, and 80% test coverage acceptance criteria.

Quick Start

Paste your rough draft prompt for any coding, research, implementation, or design task, and the skill will return a polished, ECC-aligned version ready to run immediately.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema
How do I optimize prompts for Claude Code commands and workflows?▼

To optimize prompts for Claude Code, you map vague task requests to specific ECC commands, skills, and agents, ensuring outputs include acceptance criteria, scope boundaries, and verification steps for reliable execution.

Why do my vague coding prompts fail to execute tasks properly?▼

Vague coding prompts fail because they lack the necessary context, tech stack details, and explicit scope boundaries required to leverage the Claude Code ecosystem components for reliable task execution.

How do I turn a rough draft prompt into a ready-to-run coding command?▼

You turn a rough draft prompt into a ready-to-run command by analyzing task intent, identifying missing context like tech stack and acceptance criteria, and mapping the task to appropriate ECC commands and agents.

Can I use prompt optimization for infrastructure and design tasks across any tech stack?▼

Yes, prompt optimization applies to all scenarios including coding, research, infrastructure, and design tasks across any supported tech stack and project context, delivering fully specified outputs.

What is the best way to add acceptance criteria and scope boundaries to AI prompts?▼

The best way to add acceptance criteria and scope boundaries to AI prompts is through automated intent classification and gap analysis, which structures your request with explicit do-not-do boundaries and verification steps.

Do I need prior prompt engineering experience to generate copy-paste optimized prompts?▼

No prior prompt engineering experience is needed; you simply paste your rough draft prompt, and the system automatically detects your project context to return a polished, ECC-aligned version ready to run immediately.

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