giuseppe-trisciuoglio/developer-kit Skills

Provides optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require breaking into semantically meaningful segments for embeddings and search.

Provides comprehensive CLAUDE.md file management capabilities including auditing, quality assessment, and targeted improvements. Use when user asks to check, audit, update, improve, fix, maintain, or validate CLAUDE.md files. Also triggers for "project memory optimization", "CLAUDE.md quality check", "documentation review", or when CLAUDE.md needs to be created from scratch. This skill scans all CLAUDE.md files, evaluates quality against standardized criteria, outputs detailed quality reports with scores and recommendations, then makes targeted updates with user approval.

Creates professional logical flow diagrams and logical system architecture diagrams using draw.io XML format (.drawio files). Use when creating: (1) logical flow diagrams showing data/process flow between system components, (2) logical architecture diagrams representing system structure without cloud provider specifics, (3) BPMN process diagrams, (4) UML diagrams (class, sequence, activity), (5) data flow diagrams (DFD), (6) decision flowcharts, or (7) system interaction diagrams. This skill focuses on generic/abstract representations, not AWS/Azure-specific architectures (use aws-drawio-architecture-diagrams for cloud diagrams).

Implements a complete workflow for resolving GitHub issues directly from Claude Code. Guides through the full lifecycle from fetching issue details, analyzing requirements, implementing the solution, verifying correctness, performing code review, committing changes, and creating a pull request. Use when user asks to "resolve issue", "implement issue", "work on issue #N", "fix issue", "close issue", or references a GitHub issue number for implementation. Triggers on "github issue workflow", "resolve github issue", "implement issue #", "work on issue".

This skill should be used when creating, optimizing, or implementing advanced prompt patterns including few-shot learning, chain-of-thought reasoning, prompt optimization workflows, template systems, and system prompt design. It provides comprehensive frameworks for building production-ready prompts with measurable performance improvements.

Provides patterns to build Retrieval-Augmented Generation (RAG) systems for AI applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.