Skill UI

This comprehensive pipeline guides users from a vague research concept to a fully structured, testable academic proposal. It first refines the core methodology (research-refine) to establish a stable thesis, and then generates a detailed, claim-driven experiment roadmap (experiment-plan). This end-to-end workflow ensures that the final academic output is both elegant and empirically validated.

A guide for security researchers focused on finding exploitable, remote-reachable vulnerabilities for bug bounties or responsible disclosure. It emphasizes high-signal flaws such as SSRF, RCE, and SQL injection, while guiding users through the professional triage and PoC creation process for penetration testing.

This skill provides integration with the Adaptyv Bio Foundry API, enabling the automated design, submission, and analysis of protein experiments. Users can submit amino acid sequences for various high-throughput assays, including binding kinetics (BLI/SPR), thermostability, and expression yield. It guides the entire research workflow, from sequence input to final results retrieval, accelerating biopharma discovery.

Ginkgo Cloud Lab provides remote access to an advanced autonomous lab infrastructure, enabling users to submit and manage complex molecular biology protocols. It supports diverse applications including protein expression and purification (cell-free, E. coli, Pichia), quantitative assays (HiBiT, A280, LabChip), nucleic acid synthesis (IVT mRNA/circRNA), and characterization techniques (Thermal Shift, Echo-MS, SPR). The platform features an AI agent (EstiMate) for custom workflow feasibility and pricing.

A comprehensive API wrapper for writing automated lab protocols specifically designed for Opentrons Flex and OT-2 robots. It allows users to perform complex liquid handling operations (aspirate, dispense, transfer, etc.), control various hardware modules (e.g., temperature, shaker), and manage labware and pipetting workflows, ensuring seamless integration for research and production pipelines.

Pymatgen is a comprehensive Python toolkit designed for computational materials science. It enables users to create, analyze, and manipulate complex crystal structures, calculate electronic properties (DOS, band structures), simulate phase transitions, and interact with large material databases like the Materials Project. Ideal for solid-state physics, chemistry, and advanced materials research.

This skill provides a comprehensive, multi-phase guide for authors to draft a Specification Enhancement Proposal (SEP) adhering to rigorous governance standards. It walks users through prerequisites, initial vetting (Gate), detailed interviews (e.g., breaking changes, security), and technical research, ensuring the proposed change is viable and community-vetted before formal submission.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

A comprehensive playbook detailing expert-level techniques for exploiting web cache vulnerabilities. Covers both Web Cache Deception (stealing authenticated user data) and Web Cache Poisoning (injecting malicious content). Techniques include path confusion, unkeyed header manipulation (X-Forwarded-Host), and exploiting CDN/reverse proxy caching logic. Essential reading for penetration testers and security researchers.

This sophisticated orchestrator manages the entire academic research lifecycle, guiding users from initial research concepts through drafting, structured peer review, multiple revision stages, and final integrity checks. It coordinates specialized skills to ensure a reproducible and high-quality workflow, automating the complex transition from academic idea to publication-ready manuscript.

This meta-skill orchestrates the entire academic writing workflow, from initial requirement extraction (topic, length, audience) to drafting, citation management, and final LaTeX/PDF compilation. It supports various modes, including compact skeletons for quick drafts and full manuscripts for publication-ready work. Ideal for users needing structured help with research papers or academic manuscripts.

This tool acts as a pre-drafting planning mechanism for academic or technical writing. It analyzes the user's request to extract and structure detailed preferences, such as target audience, citation style, depth, and desired emphasis. It determines the optimal generation mode (direct or preference-driven) before any writing or research takes place, ensuring all required criteria are met systematically.