research-pipeline

Automated research workflows coordinate parallel agents to investigate project dimensions like stack, features, architecture, pitfalls, and skills. This pipeline orchestrates multiple researchers and a synthesizer to produce a consolidated summary, reducing manual coordination overhead.

A multi-researcher synthesis pipeline spawns dimension-specific agents to gather structured data, then aggregates their findings into a single SUMMARY.md. It operates through a roadmapper component and enforces a repeatable workflow using templates and placeholders for context-driven research.

Yes, the pipeline runs a post-synthesis quality scoring loop that flags low-confidence results. When the scoring mechanism detects insufficient evidence or gaps, it can automatically trigger a re-research cycle to improve output reliability.

Project research outputs are structured by aggregating parallel agent findings into a SUMMARY.md file via a synthesizer. The pipeline uses templates and placeholders to enforce a repeatable workflow, enabling review and supporting evidence-based decision-making.

No, the research pipeline operates without external dependencies or components. It self-contains the orchestration logic for spawning researchers, aggregating outputs, and running quality scoring loops using internal templates and placeholders.

A coordinated research pipeline eliminates manual coordination overhead by automatically spawning five parallel researchers, aggregating their outputs, and running quality scoring. This structured approach ensures repeatable workflows and evidence-based synthesis compared to manual orchestration.