Skill UI

BGPT Paper Search queries the remote MCP server to retrieve structured experimental data from full-text studies, returning methods, results, sample sizes, quality scores, and conclusions for efficient literature reviews and evidence synthesis.

Hypogenic automates LLM-driven hypothesis generation and testing over tabular datasets, blending literature insights with empirical analysis to accelerate discovery in domains like deception detection or AI content evaluation.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

A comprehensive guide for systematic statistical analysis, designed for academic research. This skill assists in selecting the correct hypothesis tests (t-test, ANOVA, regression, chi-square), checking assumptions (normality, homogeneity), performing advanced analyses (Bayesian methods, power analysis), calculating effect sizes, and generating full APA-formatted reports for publication.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.

TorchDrug is a PyTorch-native toolbox for building graph neural networks tailored to molecules, proteins, and biomedical knowledge graphs, covering property prediction, generation, retrosynthesis, and knowledge graph reasoning with curated datasets and models.

Guides PMs through a full discovery cycle—from framing a hypothesis to validating solutions—by combining problem definition, customer interviews, synthesis, and experiments so teams can test assumptions before investing in build work.

Guides product teams to convert major initiatives into structured hypotheses that spell out the action, beneficiary, outcome, and validation steps so uncertainties surface before roadmaps or delivery planning.

Defines and documents Proof of Life probes—lightweight, disposable experiments that test a single risky hypothesis fast so teams learn harsh truth before building production software.

A structured multi-agent board meeting protocol for executives that moves through six phases—context loading, isolated role contributions, critic review, synthesis, founder review, and decision logging—to drive consistent strategic outcomes when invoking /cs:board.

Guides experts through auditing and experimenting on non-registration forms to boost completion rates, covering assessment, design, copy, layout, and hypothesis testing for lead, contact, demo, survey, or checkout flows.

This intelligent studio acts as a visual creative director, automatically routing image requests to the optimal specialized AI model. It handles hyper-realistic portrait generation (for influencers/professional photos) and advanced artistic creation, illustration, and photo manipulation (upscale, inpainting, background removal). Use it for professional content creation requiring specialized visual expertise.