Convert data between formats, schemas, or representations with explicit loss accounting and validation. Use when reformatting data, mapping between schemas, normalizing inputs, or translating structures.

Watch and report current state of a target system, process, or entity. Use when monitoring status, inspecting live systems, checking current conditions, or observing runtime behavior.

Produce a comprehensive audit trail of actions, tools used, changes made, and decision rationale. Use when recording compliance evidence, tracking changes, or documenting decision lineage.

Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.

Split work across subagents with explicit contracts, interfaces, and merge strategies. Use when parallelizing tasks, distributing workload, or orchestrating multi-agent workflows.

Ingest and parse incoming messages, events, or signals into structured form. Use when processing external inputs, handling API responses, parsing webhook payloads, or ingesting sensor data.

Frontend-specific technical decision criteria, anti-patterns, debugging techniques, and quality check workflow. Use when making frontend technical decisions or performing quality assurance.

Write stable learnings, decisions, and patterns to durable storage like CLAUDE.md or knowledge files. Use when saving project decisions, recording patterns, or updating long-term memory.

Create representation of current world state for a domain. Use when modeling system state, building world models, capturing entity relationships, or establishing baseline snapshots.

Vitest testing framework patterns and best practices. Use when writing unit tests, integration tests, configuring vitest.config, mocking with vi.mock/vi.fn, using snapshots, or setting up test...

Architectural guidance for building node-based UIs with React Flow. Use when designing flow-based applications, making decisions about state management, integration patterns, or evaluating whether...

Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches...

Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use when reviewing SQL queries, database schemas, JSONB usage, or connection management.

Reviews BubbleTea TUI code for proper Elm architecture, model/update/view patterns, and Lipgloss styling. Use when reviewing terminal UI code using charmbracelet/bubbletea.

Run what-if scenarios to explore outcomes and test hypotheses. Use when evaluating alternatives, stress-testing designs, exploring edge cases, or predicting system behavior under different conditions.

Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.

Frontend testing rules with Vitest, React Testing Library, and MSW. Includes coverage requirements, test design principles, and quality criteria. Use when writing frontend tests or reviewing test quality.

Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit,...

Agentic MCP - Three-layer progressive disclosure for MCP servers with Socket daemon. Use when the user needs to interact with MCP servers, query available tools, call MCP tools, or manage the MCP...

Request clarification when input is ambiguous. Use when user request has missing parameters, conflicting interpretations, or insufficient constraints for reliable execution.