trace-citations

What problem does it solve?

You need a structured view of how a specific research paper connects to prior work and later work, including which citations look influential, which are merely contextual, and which edges are weak signals.

Core Features & Use Cases

• Lineage discovery: Pulls strong references (foundations) and strong citing descendants around a focal paper to understand what it builds on and what it enables.
• Graph bucketing with confidence: Separates outputs into foundations, direct descendants, bridge nodes (mid-confidence connectors), weak edges (low-signal), and an optional second-hop expansion for stronger anchors.
• Context and intent signals: Uses citation contexts and intent metadata to improve interpretability and explain why edges are categorized.

Quick Start

Run: the AI assistant executes the trace-citations workflow for the paper title you specify and returns a JSON report with the citation buckets.