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connected-papers-mapper skill

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/plugins/babysitter/skills/babysit/process/specializations/domains/science/scientific-discovery/skills/connected-papers-mapper

This skill helps researchers map citation graphs to discover related work via visual traversal, temporal analysis, and bridge detection.

npx playbooks add skill a5c-ai/babysitter --skill connected-papers-mapper

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: connected-papers-mapper
description: Citation graph exploration for discovering related work through visual graph traversal
allowed-tools:
  - Bash
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - WebFetch
metadata:
  specialization: scientific-discovery
  domain: science
  category: literature-knowledge
  phase: 6
---

# Connected Papers Mapper

## Purpose

Provides citation graph exploration capabilities for discovering related work through visual graph traversal and temporal analysis.

## Capabilities

- Citation graph generation
- Seminal paper identification
- Research front detection
- Temporal citation analysis
- Field bridge identification
- Export to reference managers

## Usage Guidelines

1. **Seed Papers**: Start with key papers in the field
2. **Graph Exploration**: Navigate citation relationships
3. **Temporal Analysis**: Track field evolution over time
4. **Bridge Detection**: Find cross-disciplinary connections

## Tools/Libraries

- Connected Papers API
- NetworkX
- pyvis

Overview

This skill provides interactive citation graph exploration to help researchers discover related work by visually traversing citation relationships and temporal trends. It builds and visualizes citation networks, highlights seminal works and emerging fronts, and lets you export results to reference managers. The goal is faster literature discovery and clearer mapping of how ideas connect across time and fields.

How this skill works

Starting from one or more seed papers, the skill queries citation data and constructs a directed graph of references and citations. It computes metrics to surface seminal nodes, clusters research fronts, and detects cross-field bridges. Interactive visualizations allow zooming, filtering by year or topic, and temporal playback to watch the field evolve. Export options produce bibliographic files compatible with common reference managers.

When to use it

When you need to quickly map the literature around one or more seed papers
To identify foundational papers and rising research fronts in a topic
When exploring cross-disciplinary links or potential collaborators
To prepare literature reviews, grant proposals, or background sections
When you want bibliographic exports for citation managers

Best practices

Start with a small set of high-quality seed papers to focus the graph
Use temporal filters to separate historical foundations from recent activity
Iteratively expand the graph from promising peripheral nodes instead of blasting breadth-first
Validate detected seminal works against domain knowledge and citation counts
Export snapshots after major pruning or annotation steps for reproducibility

Example use cases

A PhD student maps citation paths from a classic paper to current hot topics to define a dissertation gap
A grant writer finds interdisciplinary bridges to justify a novel collaboration
A literature review author identifies clusters and selects representative papers for each subtopic
A PI tracks how a field shifted after a seminal publication to inform research strategy

FAQ

What input does the skill require?

Provide one or more seed paper identifiers (DOI, arXiv ID, or title). The tool then retrieves citation relationships to build the graph.

Can I export results to my reference manager?

Yes. The skill supports export formats compatible with common reference managers so you can import selected nodes and metadata.