Skill UI

Applies empirically grounded cognitive science frameworks to help CS and AI researchers generate genuinely novel directions through bisociation, analogical reasoning, constraint shifts, and problem reformulation workflows.

This comprehensive guide addresses common technical and business logic errors encountered when integrating with the Juicebox API. It covers HTTP status codes (e.g., 401, 403, 429), including authentication failures, quota exhaustion, rate limiting, data validation issues, and analysis timeouts. The resource provides detailed causes, specific fixes, and best practices for building reliable and robust integrations into recruiting and research workflows.

Provides a senior migration architect workflow that researches legacy codebases, maps bounded contexts, and writes Strangler Fig-based modernization roadmaps so other teams can incrementally reshape systems.

Provides red team workflows combining subdomain enumeration, live host discovery, technology fingerprinting, XSS hunting, API fuzzing, and automated recon scripting to support bug bounty hunters and security researchers.

Provides red team workflows combining subdomain enumeration, live host discovery, technology fingerprinting, XSS hunting, API fuzzing, and automated recon scripting to support bug bounty hunters and security researchers.

AnnData supplies a Python-native container for annotated matrices, letting researchers store measurements alongside rich metadata, read/write h5ad/zarr/loom/10X files, and integrate with the scverse tools when building single-cell or related data workflows.

Integrates with the LabArchives ELN API to programmatically manage notebooks, entries, attachments, backups, reports, and third-party tools (Protocols.io, Jupyter, REDCap) for research workflow automation.

PyTorch Lightning Toolkit streamlines PyTorch model training by organizing LightningModules, LightningDataModules, Trainer configs, callbacks, logging, and distributed strategies for scalable multi-GPU/TPU runs in research or production workflows.

Guides research teams through a two-stage manuscript workflow: outline sections with research-lookup, enforce IMRAD structure, citation styles, figures, and reporting guidelines, then convert into polished prose for journals.

A robust Python client wrapper for interacting with the Zotero Web API v3. This skill allows users to programmatically manage academic references, including retrieving, creating, updating, and deleting items, collections, tags, and attachments. Ideal for academic researchers building automated workflows, bulk exporting citations (e.g., BibTeX), or integrating Zotero data into larger research applications.

This command guides the entire lifecycle of major feature development, providing a structured, multi-phase workflow. It helps users move a feature from initial concept (research) through planning, implementation, and progress tracking. Use it when you need to coordinate status, next steps, and phased delivery for complex features.

End-to-end autonomous research workflow covering idea discovery, experiments, review, and paper submission. Supports resumable runs, optional Lean formalization, and configurable checkpoints for human oversight.