ce:plan

To convert a feature description into a structured project plan, you need to process the input text and format it into markdown. This approach applies parallel research to understand local architecture and external best practices before outputting the formatted plan.

Structuring bug fixing plans in markdown requires categorizing the issue and defining actionable steps based on complexity. The plan formatting process integrates local learnings and project patterns to ensure the resulting document aligns with your existing conventions.

Yes, you can generate project plans for new feature development using local codebase research. The planning workflow queries local learnings and framework documentation alongside external best practices to ensure the output plan reflects your specific technology stack.

You need parallel research agents to gather comprehensive context before formatting markdown project plans. These research components analyze repository structure, past learnings, and framework documentation to ensure the generated feature development plan follows accurate conventions.

Automated project planning works for issue categorization and audience targeting by analyzing issue complexity during the markdown formatting phase. It structures the feature description output to ensure the resulting plan is clear and actionable for the intended audience.

Your feature development plan may lack project convention adherence if it is generated without local and external research. Applying parallel research agents to analyze framework documentation and repository patterns ensures the output markdown follows your established project conventions.