autoconference:survey

What problem does it solve?

It automates systematic multi-database literature discovery by coordinating multiple researchers across non-overlapping sources and then synthesizing results using citation-chain knowledge transfer.

Core Features & Use Cases

• Systematic multi-database coverage: Split researchers by database, time period, methodology, or a custom partitioning strategy to reduce blind spots.
• Citation-chain knowledge transfer: Convert each researcher’s found citation leads into cross-researcher gap-filling tasks for the next rounds.
• Taxonomy-driven organization & quality checks: Enforce category-level minimum coverage targets, run peer review for summary accuracy and categorization, and track coverage metrics.
• Structured final deliverable: Produce a comprehensive survey-report.md including taxonomy tables, citation graphs, and coverage heatmaps.

Quick Start

Use autoconference:survey to run a systematic literature survey by providing your topic or research question, then confirming a partitioning strategy, taxonomy categories, and survey rounds.