Development

Python code quality standards (PEP 8, type hints, docstrings). Use when writing Python code.

PROJECT.md alignment patterns and validation strategies

Semantic validation patterns for PROJECT.md alignment (GOALS, SCOPE, CONSTRAINTS, ARCHITECTURE)

Structured logging, debugging techniques (pdb/ipdb), profiling (cProfile/line_profiler), stack traces, performance monitoring, and metrics. Use when adding logging, debugging issues, or optimizing performance.

Standardized library design patterns for autonomous-dev including two-tier design, progressive enhancement, non-blocking enhancements, and security-first architecture. Use when creating or refactoring Python libraries.

Documentation standards and automation. Use when updating docs, writing guides, or synchronizing code with documentation.

Documentation consistency enforcement - prevents drift between README.md and actual codebase state. Auto-activates when updating docs, committing changes, or working with skills/agents/commands.

This skill should be used when reviewing code or preparing code for review. It provides guidelines for what to look for in reviews, how to write constructive feedback, and standards for review comments.

This skill should be used when designing system architecture, making architectural decisions, or evaluating design patterns. It provides guidance on common patterns, ADR templates, design principles, and tradeoff analysis.

API integration patterns for autonomous-dev including subprocess safety, GitHub CLI integration, retry logic, authentication, rate limiting, and timeout handling. Use when integrating external APIs or CLI tools.

REST API design best practices, versioning strategies, error handling, pagination, and OpenAPI documentation. Use when designing or implementing REST APIs, HTTP endpoints, or API documentation.

Standardized output formats for research, planning, implementation, and review agents. Use when generating agent outputs or parsing agent responses.

Detects when user requests warrant critical analysis via /advise command

Project-specific context including project nature, technology stack, and implementation principles. Customize for each project.

Defines environment variables, architecture design, and build/test commands. Use when configuring environment or designing architecture.

Detects code smells, anti-patterns, and readability issues. Use when implementing features, reviewing code, or refactoring.

ユーザーのスキル変更要求を最適化パターン評価付きで実装

Implement user skill change requests with optimization pattern evaluation

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

Comprehensive web page validation with authentication, screenshot capture, mobile testing, and enhanced error detection

Modern web development patterns using React + Tailwind CSS + shadcn/ui for building production-quality, accessible, and performant web applications