tda-visualisation-and-diagramming

Validate and categorize academic paper figures with provenance tracking.

1|Updated Dec 13, 2025

Search Tags:#academic publishing #provenance tracking #paper review #figure validation #data reproducibility

Ready to run

npx skills add https://github.com/stephendor/TDL --skill tda-visualisation-and-diagramming

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tda-visualisation-and-diagramming
Source: https://github.com/stephendor/TDL/tree/main/.agents/skills/tda-visualisation-and-diagramming
Command: npx skills add https://github.com/stephendor/TDL --skill tda-visualisation-and-diagramming

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of creating and reviewing figures for academic papers, ensuring that they are accurate, reproducible, and adhere to best practices.

Core Features & Use Cases

Figure Classification: Automatically categorizes figures based on their intended use (e.g., paper figure, diagnostic plot).
Provenance Binding: Attaches provenance to figures, ensuring reproducibility.
Caption and Claim Validation: Checks captions and claims against underlying data.
Use Case: When a researcher needs to validate a figure's accuracy and ensure it can be regenerated from the script used to create it.

Quick Start

Apply the tda-visualisation-and-diagramming skill to validate the figure created for the paper with ID 'P01-B'.

Frequently Asked Questions about tda-visualisation-and-diagramming

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

FAQPage Schema

How do I validate academic paper figures against underlying data?▼

To validate academic paper figures, you must check captions and claims against the underlying data and attach provenance tracking. This ensures figure accuracy and confirms the results can be reproduced.

What is provenance binding for academic publication figures?▼

Provenance binding for academic publication figures is the process of attaching data provenance to visuals. This mechanism ensures data reproducibility and confirms that figure claims match the original dataset.

How do I ensure data reproducibility when reviewing paper figures?▼

To ensure data reproducibility during paper review, you must require script regeneration for each figure. This confirms the visual output can be recreated exactly from the script used to create it.

Can I automatically categorize diagnostic plots and paper figures?▼

Yes, you can automatically categorize diagnostic plots and paper figures through figure classification. This process validates the intended use of visuals to ensure adherence to publication standards.

What is the best way to track figure provenance for peer review?▼

The best way to track figure provenance for peer review is binding each visual to its underlying data and generation script. This provides verifiable evidence that figure claims are accurate and reproducible.