research-flow-navigator

AI research workflow coordination routes tasks through modular sub-skills with explicit stage boundaries and isolated handoffs. It provides a unified entry point to orchestrate the full process from idea evaluation and literature synthesis to experimental planning and results reporting.

Routing vague research ideas applies structured workflow coordination to map tasks to the most capable sub-skill. It identifies stage boundaries and blocking points to surface blockers and transition work from concept evaluation to experimental design.

Yes, workflow coordination supports end-to-end research collaboration by transitioning tasks across stages. It routes literature synthesis and experiment planning through modular sub-skills with dependency hints to ensure safe, isolated handoffs between each phase.

No, this AI research routing skill operates without external dependencies. It uses structured routing with internal references to manage stage boundaries, dependency hints, and safe handoffs across the full research chain.

Research workflows break down without explicit stage boundaries and isolated handoffs. This routing skill solves fragmentation by identifying blocking points and safely managing dependencies between modular sub-skills during task transitions.

Modular routing is unnecessary for single-stage tasks or isolated literature reviews that do not require full-chain coordination. It is designed for complex workflows needing stage boundaries, dependency hints, and structured handoffs across multiple research phases.