Full autonomous execution from idea to working code

Cancel any active OMC mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline)

Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.

Fix build and TypeScript errors with minimal changes

Multi-agent research that keeps bringing gifts back — like cats! Dispatch multiple agents to research a topic in parallel, compile findings, and iterate on new discoveries.

Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state,...

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating...

Execute multiple independent tasks simultaneously using parallel agent coordination to maximize throughput. Use when tasks have no dependencies, results can be aggregated, and agents are available...

Iterative planning with Planner, Architect, and Critic until consensus

Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware...

Run a comprehensive code review

Run a comprehensive security review on code

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Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent...

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Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or...

Self-referential loop until task completion with architect verification

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