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 asks for a thorough code review, wants a second opinion on a PR, or needs security and design issues surfaced before merging. Dispatch for review work that should be independent of the author's context.
Use when the user needs a map of an unfamiliar codebase before making changes — entry points, module boundaries, key functions, and impact analysis for a proposed change. Dispatch before touching an area no one on the current thread understands.
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.
Use when the user needs deep analysis of large document sets or multi-file cross-referencing — Teams/SharePoint hand-offs, client decks, financial models, and long PDFs. Dispatch for work that would blow out the main agent's context (20+ pages, 5+ files, multi-sheet Excel models).
Use when the user has multiple independent work streams that can run simultaneously — spawns sub-agents per stream in git worktrees, coordinates execution respecting dependencies, and returns a single consolidated summary to the main thread.