phd-research-companionv1.0.2

A PhD student starting a new research project uses the skill to create a structured research environment, including literature survey directories, experiment design templates, and LaTeX drafting folders, ensuring compliance with publication standards from day one.

A researcher conducts a comprehensive literature review by using the multi-source search module to gather and deduplicate papers from arXiv and Semantic Scholar, then analyzes them in batch mode to extract key contributions and methodologies for a meta-analysis.

A data scientist designs robust experiments by generating YAML configurations for ablation studies and baseline comparisons, then uses the revision tracker to document multiple improvement cycles before submitting results to a conference like NeurIPS.

A theoretical computer scientist uses the math notation verifier to ensure consistency in proofs and symbols across a paper draft, automating checks for errors before advisor review or journal submission to maintain scientific integrity.

An academic author runs the compliance checker before submitting a paper to IEEE TIFS, validating all requirements such as formatting, references, and traceability evidence to reduce rejection risks and streamline the publication process.

Offer a free tier with basic search and analysis features to individual students, and charge universities for premium licenses that include advanced modules like deep paper analysis, compliance checking, and team collaboration tools, generating revenue through annual subscriptions.

Sell customized enterprise licenses to large research organizations or corporations with R&D departments, providing dedicated support, integration with existing tools like Zotero, and enhanced security features, with revenue from one-time purchases or multi-year contracts.

Expose core modules such as multi-source search and paper analysis as APIs, allowing developers and academic publishers to integrate them into their platforms, charging based on usage metrics like number of API calls or processed papers.