ar-citation-verifier

Map in-text citations to verified references and classify them as verified, misrepresented, or exaggerated.

Updated Mar 22, 2026

Search Tags:#verification #citation #peer-review #reference-check #academic-writing #misrepresentation

Ready to run

npx skills add https://github.com/ShinyGua/AutoArtsResearch --skill ar-citation-verifier

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ar-citation-verifier
Source: https://github.com/ShinyGua/AutoArtsResearch/tree/main/.claude/skills/ar-citation-verifier
Command: npx skills add https://github.com/ShinyGua/AutoArtsResearch --skill ar-citation-verifier

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Citation integrity in scholarly writing is critical but frequently misrepresented or distorted. This Skill provides a repeatable workflow to verify that in-text citations accurately reflect the cited sources, reducing misattribution.

Core Features & Use Cases

Automated extraction and mapping of in-text citations to verified references.
Context-aware evaluation using reading notes, evidence units, and external sources to judge claim accuracy.
Structured output including a JSON citation_verify_report and a human-readable summary with suggested corrections.
Use Case: Journals, editors, and research teams aiming to improve citation fidelity before submission or during peer review.

Quick Start

Instruct the system to run the citation verification workflow on your draft manuscript located in the workspace.

Frequently Asked Questions about ar-citation-verifier

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I verify that in-text citations accurately reflect the cited sources?▼

To verify citation faithfulness, this Skill maps every in-text citation to its reference entry and cross-checks claims against reading notes and web sources. It classifies each citation as verified, misrepresented, or exaggerated and outputs a human-readable summary with suggested corrections.

How do I check my academic paper for citation misrepresentation before submission?▼

Checking academic writing for citation misrepresentation involves evaluating context against evidence units and external sources. This workflow identifies exaggerated or distorted claims, generating a machine-readable citation_verify_report.json to ensure citation fidelity during peer review.

What is the best way to automate reference checks for scholarly writing?▼

Automating reference checks is best handled by extracting and mapping in-text citations to verified references. This process evaluates claim accuracy using reading notes and evidence units, producing a structured JSON report and a summary with suggested corrections for journals and research teams.

Does this citation verification workflow require external dependencies or components?▼

This citation verification workflow does not require external dependencies or components. It operates as an Advanced Skill within the workspace, using your draft manuscript and available reading notes to evaluate citation integrity and generate the verification report.

How do I generate a machine-readable citation verification report for peer review?▼

Generating a machine-readable citation verification report requires mapping in-text citations to references and cross-checking claims. The workflow outputs a citation_verify_report.json file alongside a human-readable summary containing suggested corrections for misattributed information.

Can I use this Skill to assess citation fidelity for large research teams?▼

You can use this Skill to assess citation fidelity for research teams aiming to improve accuracy before submission. The workflow handles context-aware evaluation using reading notes and external sources, classifying citations to ensure scholarly writing meets peer-review standards.