Analyzes project structure, module dependencies, imports, and entry points to generate architecture diagrams in Mermaid format
Analyzes ETL and data pipeline code for optimization opportunities across Python (Pandas, PySpark), Rust (polars, datafusion), SQL, and general pipeline descriptions
Validates environment variable configurations and config files (YAML, TOML, JSON, .env) for missing required variables, type mismatches, deprecated keys, naming convention violations, secret exposure risks, and invalid value ranges
Analyzes code for performance bottlenecks including N+1 queries, O(n^2) or worse algorithms, unnecessary allocations, sync I/O in async contexts, excessive cloning, missing caching opportunities, and large payload transfers. Supports Rust, Python, TypeScript, and Go.
Analyzes, improves, and restructures LLM prompts for clarity, efficiency, and reliability
Analyzes source code for common security vulnerabilities including SQL injection, XSS, command injection, hardcoded secrets, insecure deserialization, path traversal, and SSRF
Agent reviews its own work before presenting to the user. Catches errors, style violations, and omissions before the user sees the output.
Analyzes multi-step workflows and agent pipelines for bottlenecks, unnecessary serialization, and optimization opportunities