Skill UI

This skill enables the development of robust, event-driven pipelines interacting with the Perplexity Sonar API. Since Perplexity lacks native webhooks, this system simulates event patterns using advanced techniques: Streaming Server-Sent Events (SSE) for real-time data, job queues (like BullMQ/SQS) for asynchronous batch research, and cron-triggered monitoring for scheduled news and trend alerts. It provides patterns for building complex, reliable, and scalable AI applications.

This skill provides a robust, Manus-style workflow for AI coding and research agents. By utilizing persistent markdown files (`task_plan.md`, `findings.md`, `progress.md`) stored in the project directory, it ensures that complex, multi-step work survives context loss, session restarts, and tool clearing. It guides the user through structured planning, logging, and recovery, making it ideal for large projects or deep research tasks.

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.

Defines the Research Engineer role, focused on investigating problems, prototyping solutions, and bridging research with engineering execution even when detailed documents are unavailable.

This skill provides a comprehensive, expert guide to the entire reverse engineering lifecycle. It covers advanced techniques for binary analysis, including static analysis (disassembly, metadata extraction, control flow mapping) and dynamic analysis (API hooking, memory tracing). Mastery includes utilizing industry-leading tools such as IDA Pro, Ghidra, radare2, and specialized frameworks like pwntools and angr. The methodology is structured for secure research, CTF challenges, and vulnerability assessment, emphasizing best practices and ethical use.

This guide demonstrates how to implement robust Role-Based Access Control (RBAC) and financial governance for cloud GPU environments. It allows organizations to allocate resources, set team-specific budgets, whitelist approved GPUs, and track spending via detailed audit logs. Ideal for multi-team research and engineering environments requiring strict cost accountability and access separation.

This skill simulates an expert software engineer and systems analyst. It is designed for deep, evidence-based understanding of complex codebases. Users can ask "how does X work" or request architectural reviews, ensuring every claim is grounded in actual code paths, data flows, and dependency chains, following a rigorous multi-iteration process.

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.

gget is a CLI/Python client that unifies querying over 20+ bioinformatics databases, letting researchers fetch gene info, sequences, BLAST results, structures, and enrichment data interactively or within scripts.

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.