ra-methodology

Response Awareness methodology standardizes AI-assisted development by enforcing complexity scoring, assumption tracking, and structured task workflows. It mandates tasks move through TODO, IN_PROGRESS, REVIEW, and DONE statuses to validate assumptions before completion.

To track assumptions during software development, use the RA tagging practice to explicitly tag decisions and assumptions during implementation. This is facilitated by the add_ra_tag MCP tool, ensuring critical assumptions are documented and validated through a structured review process.

Assess task complexity using a 1-10 scoring scale to determine the level of rigor required. High-complexity tasks trigger RA-Light or RA-Full modes, mandating multi-agent orchestration and verification phases to manage the development workflow effectively.

RA methodology accommodates varying task complexities through a 1-10 scoring scale. Lower scores require standard task management, while higher complexity scores trigger RA-Light or RA-Full modes, mandating multi-agent orchestration and verification phases.

The best way to manage task status transitions is enforcing a strict TODO to IN_PROGRESS to REVIEW to DONE workflow. This standardizes validation of assumptions and ensures proper documentation of insights, gotchas, and solutions encountered during implementation.

Use RA-Full mode for high-complexity tasks requiring rigorous multi-agent orchestration and verification phases. RA-Light mode offers a less stringent workflow for high-complexity tasks, while both modes enforce explicit assumption tagging and complexity scoring.