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From developer-kit-ai
Optimizes input prompts for LLMs using CoT, few-shot, constitutional AI, and model-specific techniques. Saves optimized prompt to optimized-prompt.md and generates assessment report.
npx claudepluginhub giuseppe-trisciuoglio/developer-kit --plugin developer-kit-aiHow this command is triggered — by the user, by Claude, or both
Slash command
/developer-kit-ai:devkit.prompt-optimize [prompt-text] [target-model] [optimization-level]sonnetThis command is limited to the following tools:
The summary Claude sees in its command listing — used to decide when to auto-load this command
# Prompt Optimization ## Overview Provides expert prompt optimization using advanced techniques (CoT, few-shot, constitutional AI) for LLM performance enhancement. Use when you need to improve prompt quality or optimize LLM interactions. You are a prompt engineering expert specializing in transforming basic instructions into production-ready prompts using advanced techniques. ## Usage ## Arguments | Argument | Description | |--------------|------------------------------------------| | `$ARGUMENTS` | Combined arguments passed to the command | ## Execu...
/prompt-optimizeOptimizes input prompts for LLMs using chain-of-thought, few-shot examples, constitutional AI self-critique, and model-specific patterns for production readiness.
/optimize-promptRewrites and optimizes an AI prompt using structured best practices like sectioning, examples, chain-of-thought, and guardrails, producing an annotated improved version.
/promptCrafts and reviews prompts for subagents and humans. Default FIX mode outputs improved prompt; REVIEW mode gives analysis and verdict.
/new-promptBuilds new prompts from parameters or optimizes existing ones using Anthropic's best practices, producing structured enhanced prompts with improvements.
/reprompt-oratorOptimizes a prompt using Anthropic best practices, scoring across 7 dimensions (clarity to tone), listing applied techniques, and returning a restructured prompt.
/promptEngineers, tests, versions, and optimizes LLM prompts using patterns like few-shot, CoT, ReAct; produces YAML specs, MD prompts, examples, test suites, evaluations, and git commits. Also supports optimize, test, compare flags.
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Provides expert prompt optimization using advanced techniques (CoT, few-shot, constitutional AI) for LLM performance enhancement. Use when you need to improve prompt quality or optimize LLM interactions. You are a prompt engineering expert specializing in transforming basic instructions into production-ready prompts using advanced techniques.
/devkit.prompt-optimize $ARGUMENTS
| Argument | Description |
|---|---|
$ARGUMENTS | Combined arguments passed to the command |
Agent Selection: To execute this prompt optimization task, use the following agent with fallback:
developer-kit-ai:prompt-engineering-expertdeveloper-kit-ai:prompt-engineering-expert or fallback to general-purpose agent with prompt
engineering expertiseExtract and optimize the prompt provided in the arguments: $ARGUMENTS
Target Model: $2 (default: claude-3.5-sonnet) Optimization Level: $3 (default: standard)
Available optimization levels:
basic - Quick improvements (structure, clarity, basic CoT)standard - Comprehensive enhancement (CoT, few-shot, safety)advanced - Production-ready (full optimization with testing framework)Apply the prompt-engineering-expert agent to optimize the prompt using:
Advanced Techniques:
Model-Specific Optimization:
The prompt-engineering-expert agent MUST provide:
Complete Optimized Prompt:
optimized-prompt.mdOptimization Report:
Implementation Guidelines:
For Document Analysis Tasks:
For Code Comprehension Tasks:
For Multi-Step Reasoning:
The optimized prompt must:
/devkit.prompt-optimize example-input