The Hacker News community is buzzing over a new GitHub project called Use-Citations, a specialized skill designed to transform Claude Code from a generic coding assistant into a rigorous research engine. Developed by user sshah03, this tool targets developers and researchers who need auditable answers in high-stakes fields like law, tax, and medicine. By integrating directly into the Claude Code shell, it addresses the persistent AI hallucination problem by forcing the model to ground every response in verifiable source documents.

How It Works

Unlike standard LLM interactions that generate text from parametric memory, Use-Citations instructs Claude to actively save the source documents used during a query. The skill then constructs a structured artifact or report where each claim is explicitly linked to its corresponding evidence. This mechanism ensures that users can trace the lineage of any answer back to the original text, effectively turning the coding environment into a citation-backed knowledge base.

Targeting High-Stakes Research

While Claude Code is primarily optimized for software development, its underlying architecture is capable of handling complex knowledge-based queries. The creator specifically highlights the tool's utility for professionals in law, tax, and medicine, where accuracy is non-negotiable. By leveraging the shell environment, researchers can ask intricate questions and receive answers that are not just plausible, but provable, reducing the cognitive load of manual verification.

Key Takeaways

  • The tool is open-source and available on GitHub under the repository sshah03/use-citations.
  • It functions as a skill within the Claude Code interface, requiring no external API changes.
  • The primary output is a report artifact that maps specific answers to saved source documents.
  • It is particularly useful for fields where hallucinations can have significant professional consequences.

The Bottom Line

This skill represents a necessary evolution for AI coding tools. We don't just want code that compiles; we want answers that hold up in court, in the clinic, and in the boardroom. Use-Citations is a small step toward making AI agents truly trustworthy partners in rigorous research.