Summary

CitationClaw addresses the challenge of quantifying and explaining the impact of scientific citations. It provides researchers and power users with a lightweight engine to generate comprehensive citation portrait reports, identifying influential scholars and visualizing impact. The tool aims to turn every citation into explainable influence, offering rapid analysis and actionable insights.

How It Works

The system employs a deterministic five-phase pipeline: crawling citation data, performing author intelligence analysis, exporting results, generating citing descriptions via LLMs, and finally, creating a shareable dashboard report. This logic is orchestrated through a skills-style runtime, allowing modular execution of distinct functionalities. This approach enables flexibility and maintainability while processing complex citation networks.

Quick Start & Requirements

Installation is straightforward via pip install citationclaw. Python 3.10+ is required, with 3.12 recommended. Essential prerequisites include API keys for ScraperAPI (for web crawling) and an OpenAI-compatible service (for LLM-based analysis), which may incur costs. Official documentation and quick-start guides are available online at https://visionxlab.github.io/CitationClaw/.

Highlighted Details

• Five-Phase Pipeline: A structured workflow encompassing data fetching, author analysis, export, LLM-driven descriptions, and report generation.
• Renowned Scholar Focus: Automatically identifies and prioritizes outputs for high-impact researchers.
• Tiered Analysis Modes: Offers Basic, Advanced, and Full modes to balance analysis depth against speed and cost.
• Resumable & Cache-Aware: Supports resuming interrupted analyses and leverages caching for authors and descriptions to improve efficiency.
• Shareable HTML Report: Generates standalone HTML dashboards for easy viewing and sharing without requiring a server.

Maintenance & Community

CitationClaw is community-driven and actively encourages contributions via Pull Requests, with specific areas identified for "good first tasks." Recent updates in March 2026 indicate ongoing development, including a public v1.0 release. A Chinese user group is available, and community guidelines are provided at https://github.com/VisionXLab/CitationClaw/pulls.

Licensing & Compatibility

The project is licensed under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0 International). This license strictly prohibits commercial use, limiting its applicability for integration into commercial products or services.

Limitations & Caveats

The primary limitation is the CC BY-NC 4.0 license, which restricts commercial applications. Users must provide and manage external API keys for ScraperAPI and LLM services, potentially incurring operational costs. As of its first public release (v1.0), the project may still be undergoing refinement, and LLM outputs are subject to inherent model limitations.