Provides a quality framework and enforceable conventions for AI coding assistants, ensuring code quality, environment hygiene, and project standards across multiple AI tools.
Enables AI assistants to manage project analysis, code metrics, documentation, Git operations, code quality, and file organization through natural language commands.
Provides tools to manage, initialize, and synchronize standardized agent configurations and specialized workflows across various projects. It enables AI agents to access global rules and role-specific guidelines for development, design, and planning via the Model Context Protocol.
Provides AI agents with queryable, version-controlled project rules and coding standards. Enables validation, rule-based guidance, and task summaries to keep AI work aligned with your project's conventions without repeating context.
Provides AI agents with structured access to project conventions, technology stacks, and architectural patterns to ensure consistency across development teams.
Provides unified development tools including code analysis, debugging, refactoring, documentation, testing, and project automation through multiple LLM providers (KIMI, GLM, OpenRouter). Features agentic audit capabilities with multi-model consensus for finding issues and generating direct fixes.