pipeline-planner

To map acceptance criteria to implementation parts, you need a planning process that researches codebase patterns and dependency graphs. This approach surfaces integration points and traces each criterion to concrete code structures, producing an aligned architecture plan document.

Automating phase 1 planning involves using deep analysis models to research your codebase and design solutions. It coordinates design context and code patterns to generate a concrete plan document with architecture decisions, AC mapping, and a test plan.

Yes, you can enrich codebase architecture planning with optional design-context integration. By supplying design assets like Figma files, the planning process can align UI dependencies and design context directly with the proposed implementation structure.

Yes, you need a task key and task-analysis data to generate a plan document for API and UI dependencies. This data drives the deep analysis required to map integration points and produce handoff-ready artifacts like the architecture decisions and test plan.

A limitation when planning code changes for complex architectures is the reliance on pre-existing task-analysis data to drive the deep analysis. The planning process also requires an opus model to process dependency graphs and design context effectively.

Your plan document needs AC mapping and handoff artifacts to ensure traceability from acceptance criteria to implementation parts. This mapping provides developers with concrete architecture decisions and test plans, ensuring execution aligns with the original design context.