deep-research

This Skill automates citation-backed research report generation through an eight-phase pipeline, performing parallel retrieval, triangulation, and synthesis to output a complete Markdown report with a bibliography.

Source triangulation in automated research cross-references multiple retrieved data points to validate findings, ensuring source diversity and high credibility scores before the synthesis phase.

Yes, you can run deep research workflows using only Python stdlib, as the pipeline operates autonomously without external dependencies to manage progressive context loading and retrieval.

Yes, the pipeline supports parallel retrieval across 10+ sources and offers Quick, Standard, Deep, and UltraDeep modes to control the depth of autonomous enterprise research and analysis.

The best way to ensure source credibility is using an autonomous pipeline with built-in automated validation and scoring, which checks citation integrity and source diversity before packaging the report.

To initiate standard research analysis with minimal prompts, execute the command to use deep research in standard mode, triggering the autonomous eight-phase workflow from scoping to packaging.