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paper-graph

Map the genealogical lineage and historical progression of a research field. Visualize how earlier technical challenges led to later approaches and improvements, producing a Markdown report with embedded Mermaid diagrams. Trigger when the user asks for a topic's developmental trajectory, a model's family tree, significant predecessors or follow-ups to a seed paper, or how a research line matured over time. Do not trigger for inventories of datasets, benchmarks, libraries, or other artifacts; finding one latest paper; simple keyword search; one-paper summaries; or head-to-head comparisons. Use this skill for chronological synthesis across multiple works, not for bibliography cataloging or one-off retrieval.

skills/paper-graph/SKILL.md

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Oct 27, 2026
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Apache-2.0

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# Paper Graph

Build a Markdown report with embedded Mermaid diagrams showing how research on a user-specified topic (or paper) evolved — clustered into challenges → solutions and traced as per-solution evolution paths.

The skill has no outbound LLM dependency. The host agent provides all LLM calls; the skill provides deterministic data fetchers (S2 / DeepXiv), prompt templates, markdown parsers, and Mermaid renderers. Run the runbook below step-by-step.

**Execution requirement.** When the caller already provides `parsed_query.json`, `seed.json` and `papers.json` (wherever they are, for example in an `input/` directory), copy them into the workdir under those names, treat steps 1–5 as complete and start at step 6. Still run every deterministic CLI step from classify through assemble; do not replace parsing, edge audit, rendering, or assembly with hand-authored Mermaid. Before finishing, verify that every parsed solution has a detail render and an audit verdict file, even when that file is an empty JSON list. Treat `assemble_report` as the only final-report writer: do not edit or append hand-authored edges afterward, even when a caller asks to display uncertain relationships. Preserve uncertainty in verdict JSON.

## When to Use This Skill

Trigger when the user asks something like:

- "Show me the history of <topic>" / "How did <topic> evolve?"
- "Where does <paper> stem from?" / "What did <paper> build on?"