What problem does it solve?
It converts your existing papers, notes, and web sources into a structured research wiki and prepares a final, curated paper set for ingestion.
Core Features & Use Cases
- Deterministic preparation + source manifesting: normalizes user PDFs into prepared artifacts under raw/tmp/ and writes recovery-aware manifests for traceable re-runs.
- Planner-guided discovery with trimming: ranks and trims candidate papers to a final target set (typically 8–10) using the project’s discovery tool, then records the shortlist and final selection before fetch.
- Parallel ingestion fan-out/fan-in: scaffolds wiki structure first, then ingests papers via isolated /ingest worktree subagents and merges results safely with deduplication and rebuild steps.
- Resilient recovery and reporting: checkpoints each stage, continues through partial failures, and refreshes visualization artifacts without failing the init run.
Quick Start
Run /init with your research direction keywords (optional) to scaffold wiki/ and ingest the final paper set in parallel from raw/papers/, raw/notes/, and raw/web/.