developer-kit

Provides patterns to configure AWS RDS (Aurora, MySQL, PostgreSQL) with Spring Boot applications. Configures HikariCP connection pools, implements read/write splitting, sets up IAM database authentication, enables SSL connections, and integrates with AWS Secrets Manager. Use when setting up RDS connections in Spring Boot, configuring connection pooling, or managing database credentials securely.

Provides AWS SAM bootstrap patterns: generates `template.yaml` and `samconfig.toml` for new projects via `sam init`, creates SAM templates for existing Lambda/CloudFormation code migration, validates build/package/deploy workflows, and configures local testing with `sam local invoke`. Use when the user asks about SAM projects, `sam init`, `sam deploy`, serverless deployments, or needs to bootstrap/migrate Lambda functions with SAM templates.

Provides Amazon Bedrock patterns using AWS SDK for Java 2.x. Invokes foundation models (Claude, Llama, Titan), generates text and images, creates embeddings for RAG, streams real-time responses, and configures Spring Boot integration. Use when asking about Bedrock integration, Java SDK for AI models, AWS generative AI, Claude/Llama invocation, embeddings for RAG, or Spring Boot AI setup.

Provides AWS SDK for Java 2.x client configuration, credential resolution, HTTP client tuning, timeout, retry, and testing patterns. Use when creating or hardening AWS service clients, wiring Spring Boot beans, debugging auth or region issues, or choosing sync vs async SDK usage.

Provides Amazon DynamoDB patterns using AWS SDK for Java 2.x. Use when creating, querying, scanning, or performing CRUD operations on DynamoDB tables, working with indexes, batch operations, transactions, or integrating with Spring Boot applications.

Provides AWS Key Management Service (KMS) patterns using AWS SDK for Java 2.x. Use when creating/managing encryption keys, encrypting/decrypting data, generating data keys, digital signing, key rotation, or integrating encryption into Spring Boot applications.

Provides AWS Lambda patterns using AWS SDK for Java 2.x. Use when invoking Lambda functions, creating/updating functions, managing function configurations, working with Lambda layers, or integrating Lambda with Spring Boot applications.

Provides AWS messaging patterns using AWS SDK for Java 2.x for SQS queues and SNS topics. Handles sending/receiving messages, FIFO queues, DLQ, subscriptions, and pub/sub patterns. Use when implementing messaging with SQS or SNS.

Provides AWS RDS (Relational Database Service) management patterns using AWS SDK for Java 2.x. Use when creating, modifying, monitoring, or managing Amazon RDS database instances, snapshots, parameter groups, and configurations.

Provides Amazon S3 patterns and examples using AWS SDK for Java 2.x. Use when working with S3 buckets, uploading/downloading objects, multipart uploads, presigned URLs, S3 Transfer Manager, object operations, or S3-specific configurations.

Provides AWS Secrets Manager patterns for AWS SDK for Java 2.x, including secret retrieval, caching, rotation-aware access, and Spring Boot integration. Use when storing or reading secrets in Java services, replacing hardcoded credentials, or wiring secret-backed configuration into applications.

Generates a structured Bug Fix Brief (BFB) to document issue corrections. Includes root cause analysis, repro steps, fix options, and fix checklist. Use when user asks to create a BFB, document a bug fix, or generate a bug correction document.

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 systems, vector databases, or processing large documents.

Provides automated documentation updates by analyzing git changes between the current branch and the last release tag. Performs git diff analysis to identify modifications, then updates README.md, CHANGELOG.md following Keep a Changelog standard, and discovers documentation folders for contextual updates. Use when preparing a release, maintaining documentation sync, or before creating a pull request. Triggers on "update docs", "update changelog", "sync documentation", "update readme", "prepare release documentation".

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).

Provides a structured 8-phase workflow for resolving GitHub issues in Claude Code. Covers fetching issue details, analyzing requirements, implementing solutions, verifying correctness, performing code review, committing changes, and creating pull requests. Use when user asks to resolve, implement, work on, fix, or close a GitHub issue, or references an issue URL or number for implementation.

Provides autonomous project pattern learning by analyzing the codebase to discover development conventions, architectural patterns, and coding standards, then generates project rule files in .claude/rules/. Use when user asks to "learn from project", "extract project rules", "analyze codebase conventions", "discover project patterns", or wants to auto-generate Claude Code rules for the current project.

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

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 prompts, prompt templates, or asks how to get better results from an LLM.

Posts review findings from a JSON file as inline comments on a GitHub Pull Request, attaching each comment to its file and line. Use when you have a list/JSON of review findings (each with a file path, line number, and a message such as summary/failure_scenario) and want them published on a PR as inline review comments. Triggers include "post these review comments on the PR", "associate comments to files in the PR", "publish review findings to PR