Audits a project code THROUGH its Pipeline/ doc — reads a pipeline .md and its code together, then hunts for genuine bugs (correctness, sign/normalization, convention violations) and concrete optimizations (redundant recomputation, missing memoization, complexity blow-ups). Use to review a documented code for…
Use when the user needs deep analysis of recent code changes for bugs, logic errors, or regressions — tracing execution paths across multiple files to find issues before they reach production. Distinct from code-reviewer (which reviews PRs); this agent hunts specific change sets for defects.
Use proactively when the user proposes, reviews, or refactors cloud infrastructure — Terraform spanning AWS, GCP, or Azure; CI/CD pipelines; networking; IAM; observability. Evaluates portability, security, cost, and long-term operability.
Use when the user is building or debugging a data pipeline, ETL process, data transformation, or data quality check — ingesting from APIs, files, or databases and loading to a warehouse or downstream store.