plan

To turn vague requirements into an execution plan, you normalize user inquiries into structured specifications, apply quality gates, and generate a traceable GRANULAR_EXECUTION_PLAN.md with tasks.json.

The best way to structure complex queries is to consolidate research and specifications through parallel exploration, enforcing dependency constraints to produce parseable tasks.json files ready for automated execution.

Dependency management enforces strict constraints during plan generation, ensuring task traceability and parseability so that downstream execution follows the correct sequence defined in your tasks.json.

You can validate execution readiness by reviewing the generated VALIDATION_SUMMARY.md, which confirms that all quality gates are passed and dependency constraints are met before triggering the pipeline.

You do not need to manually check quality gates when converting documentation into tasks, because the planning process automatically enforces quality gates and model selections to ensure parseable, traceable plans.

You should avoid automated planning workflows for simple, single-step requests that lack complex dependencies, as the overhead of generating validation reports and structured tasks.json files provides no benefit.