Protein design requires experimental validation. Adaptyv provides API access to a cloud laboratory for automated testing of binding affinity, expression levels, thermostability, and enzyme activity. Get experimental results in approximately 21 days.

Researchers need efficient access to computational protein structure predictions for drug discovery and structural biology studies. This skill provides direct access to AlphaFold DB's 200M+ AI-predicted protein structures, enabling retrieval by UniProt ID, download of coordinate files, and analysis of confidence metrics.

Research branches pile up and become difficult to manage. This skill automatically detects, merges, and organizes research findings from Claude Code Web sessions into actionable GitHub issues.

Developers often struggle with outdated or incomplete documentation when working with software libraries. The Context7 skill connects to the Context7 API to retrieve up-to-date documentation, code examples, and API references for any supported library or framework.

Finding accurate information online and extracting relevant content from web pages is time-consuming. This skill connects Claude to powerful AI search engines like Tavily and Exa for instant research and content extraction.

This skill enables AI agents to search the web and extract content from URLs using Tavily and Exa AI-powered search APIs. It provides research capabilities for fact-checking, content aggregation, and building RAG pipelines.

This skill provides a structured framework for competitive analysis, guiding users through feature comparisons, SWOT analysis, pricing benchmarks, and market positioning to inform product strategy.

AI agents and researchers often produce responses without current information or sources. This skill enables RAG pipelines that combine real-time web search with LLMs to generate accurate, sourced, and verifiable responses.

Standard web search tools return only snippets. This skill performs web searches and optionally extracts full page content in markdown format for deeper analysis.

This skill provides documentation for running prefill sensitivity analysis to measure how easily AI models can be manipulated into generating exploit code. Researchers use it to compare token-count versus logprob metrics for predicting reward hacking susceptibility across model checkpoints.

Finding qualified leads takes hours of research and guesswork. This skill analyzes your product and target market to identify companies that match your ideal customer profile, then provides prioritized leads with personalized contact strategies.

Understanding competitor advertising strategies helps you create more effective campaigns. This skill provides a structured approach to researching and analyzing competitor ads from public ad libraries to discover what messaging and creative approaches resonate with your target audience.

Finding accurate, up-to-date information online can be time-consuming. The Exa skill uses neural search technology to deliver high-quality, relevant web results through simple API calls.

Developers waste hours scrolling through GitHub repositories trying to find relevant issues or solutions. This skill provides structured search strategies, syntax examples, and workflow guides to quickly locate issues, pull requests, discussions, and code examples across any repository.

Agent frameworks vary widely in error handling and recovery capabilities. This skill provides systematic methods to trace error propagation, evaluate sandboxing effectiveness, and assess production readiness before deployment.

Understanding tool interfaces is critical for AI agent framework design. This skill analyzes how frameworks model, register, and execute tools with proper error handling. Use it to evaluate schema generation approaches, trace error feedback loops, and compare tool interfaces across frameworks.

Understanding how agents coordinate is critical for building scalable multi-agent systems. This skill provides frameworks and templates to analyze coordination models, handoff mechanisms, state sharing patterns, and communication protocols in any multi-agent architecture.

Agent frameworks struggle with context overflow and memory management. This skill provides systematic analysis of context assembly, eviction policies, and token budgeting strategies across different implementations.

Understanding how agent frameworks communicate with LLMs is essential for debugging, integration, and building new systems. This skill provides structured analysis methods to examine message formats, tool encoding, streaming mechanics, and multi-provider abstraction patterns.

Understanding how agent frameworks implement reasoning requires tracing complex control flows. This skill provides pattern signatures and extraction methods to identify reasoning topologies like ReAct, Plan-and-Solve, Reflection, and Tree-of-Thoughts from framework source code.