Building self-learning AI agents requires implementing complex reinforcement learning algorithms from scratch. AgentDB Learning Plugins provides ready-to-use access to nine proven algorithms including Decision Transformer and Q-Learning, enabling you to train autonomous agents that improve through experience.

Build sophisticated multi-agent AI systems with sub-millisecond database synchronization and advanced search capabilities. AgentDB Advanced Features enables distributed vector databases with custom metrics, hybrid search, and QUIC networking for production-scale AI applications.

Building AI agents with consistent, high-quality performance requires deep domain knowledge and optimized system prompts. This skill provides a structured 4-phase methodology to create production-ready agents with embedded expertise.

Building distributed vector search systems requires complex infrastructure setup. This skill provides a 5-phase implementation guide for AgentDB with QUIC synchronization, custom distance metrics, and production-ready monitoring.

Engineers struggle to break complex features into manageable steps. This skill creates granular implementation plans with test-driven development built into every task.

Complex problems require deeper thinking to avoid costly mistakes. This skill automatically detects when to use maximum reasoning depth by evaluating complexity factors like architecture decisions, multi-file changes, and security implications.

Writing tests after code proves nothing about correctness. This skill enforces the RED-GREEN-REFACTOR cycle to ensure every feature has a failing test first. Write minimal tests, verify they fail, implement the simplest code to pass, then refactor with confidence.

Debugging without a systematic approach leads to wasted time and new bugs. This skill provides a four-phase methodology to find root causes before attempting fixes, dramatically improving first-time fix success rates.

Complex development plans often fail due to accumulated context errors and missing quality checks. This methodology ensures each task gets a fresh subagent with clean context, followed by mandatory code review before proceeding.

Developers often struggle with when and how to request effective code reviews. This skill provides templates, workflows, and guidance for requesting and processing code reviews that catch issues before they compound.

Stop solving problems one at a time. This skill helps you dispatch multiple AI agents to tackle independent issues simultaneously, cutting resolution time dramatically. Perfect for when you are facing multiple test failures or unrelated bugs across different parts of your codebase.

Implementing complex plans without checkpoints leads to accumulated errors and wasted work. This skill enforces systematic execution with batch processing, verification steps, and human review points between work chunks.

Vague requirements lead to costly rework and missed deadlines. This skill transforms rough ideas into validated designs through Socratic dialogue, ensuring clarity before implementation begins.

Ruby projects need type safety for reliable code. This skill adds Sorbet inline type signatures to methods using sig blocks. It analyzes Ruby source files, generates proper type annotations, and validates signatures with the Sorbet type checker.

An AI skill for Claude, Codex, and Claude Code

Ruby lacks built-in type annotations, making code harder to understand and maintain. This skill adds RBS-inline type comments directly to your Ruby files, improving code clarity without requiring separate .rbs signature files.

This skill generates RBS type signatures for Ruby code from scratch. It analyzes Ruby source files and creates corresponding .rbs signature files with proper type definitions.

Building applications with Prisma ORM v7 requires understanding new ESM requirements, driver adapters, and configuration changes. This skill provides expert guidance on schema design, migrations, client queries, and migrating from v6 to v7.

Code reviews generate long lists of issues that are tedious to fix manually. This skill processes review documents systematically, letting you fix or skip each issue while tracking progress and running quality checks.

Writing clear, comprehensive PR descriptions takes significant time and effort. This skill automates the creation of reviewer-friendly descriptions using structured formatting, visual diagrams, and organized sections.