agent-hive

Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Use when working with Docker containers — debugging container failures, writing Dockerfiles, docker-compose for integration tests, image optimization, or deploying containerized applications

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Use when you need parallel, read-only exploration with the agent tool (Scout fan-out)

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when implementing any feature or bugfix, before writing implementation code

Use when you have a spec or requirements for a multi-step task, before touching code

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Use when you need parallel, read-only exploration with the agent tool (Scout fan-out)

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when implementing any feature or bugfix, before writing implementation code

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Use when you have a spec or requirements for a multi-step task, before touching code

Use when bootstrapping, updating, or reviewing AGENTS.md — teaches what makes effective agent memory, how to structure sections, signal vs noise filtering, and when to prune stale entries

Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when working with Docker containers — debugging container failures, writing Dockerfiles, docker-compose for integration tests, image optimization, or deploying containerized applications

Use ast-grep MCP tools for syntax-aware structural search, AST inspection, rule testing, and structural verification. Triggers: code-shape queries, structural invariants, pattern debugging, AST inspection, and multi-file syntax matching.

Use when you have a spec or requirements for a multi-step task, before touching code

Use when independently verifying implementation claims, post-merge review, or when a reviewer needs to falsify success assertions with command-and-output evidence

Use when you need parallel, read-only exploration with task() (Scout fan-out)

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Use when working with Docker containers — debugging container failures, writing Dockerfiles, docker-compose for integration tests, image optimization, or deploying containerized applications

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Use when bootstrapping, updating, or reviewing AGENTS.md — teaches what makes effective agent memory, how to structure sections, signal vs noise filtering, and when to prune stale entries

Use when implementing any feature or bugfix, before writing implementation code

Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when reviewing implementation changes against an approved plan or task (especially before merging or between Hive tasks) to catch missing requirements, YAGNI, dead code, and risky patterns

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes