claude

developer-kit-ai

AI/ML skills including prompt engineering, RAG, and chunking strategies

370 on GitHubby Giuseppe Trisciuogliov4.0.1MITupdated 2 months ago
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Plugin developer-kit-ai from marketplace developer-kit in giuseppe-trisciuoglio/developer-kit. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (3)

  • chunking-strategy

    Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation

  • prompt-engineering

    Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection, chain-of-thought structuring, system prompt design, and template composition. Use when the user asks to write or improve a prompt, wants help with few-shot examples, chain-of-thought, system prom

  • rag

    Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.

Slash commands (1)

  • /developer-kit-ai:devkit.prompt-optimize

    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.

Subagents (1)

  • prompt-engineering-expert

    Provides expert prompt engineering capabilities specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use PROACTIVELY for prompt creation, optimization, document/code analysis prompts, or

View source on GitHub

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