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.
Captures code modifications via AST analysis, generates reusable rules, and injects them into AI agent context with version audit and token-budgeted rule retrieval.
Transforms static coding standards into a queryable live data store for AI agents, delivering task-specific rules and fix guidance on demand. This optimizes context window usage through progressive disclosure, ensuring agents apply relevant governance without loading massive documentation.
MCP server for storing and retrieving context-specific agent rules, enabling AI agents to access relevant guidelines efficiently and reduce context window usage.
Provides centralized security instructions for AI-assisted code generation by matching context-aware rules to the user's programming language and file patterns. It ensures generated code adheres to security best practices without requiring manual maintenance of instruction files across individual repositories.
