Skill UI

This skill details advanced techniques for enhancing the effective context capacity of LLMs. It outlines four core strategies—Compaction, Observation Masking, KV-Cache Optimization, and Context Partitioning—to prevent context limits from constraining task complexity. By strategically managing token usage, users can reduce operational costs, minimize latency, and implement robust, long-running agent systems for handling large documents or conversations.

Master the creation of autonomous AI agents using LangChain. This guide covers defining tools with schemas (Zod), utilizing `createToolCallingAgent` and `AgentExecutor` for multi-step decision-making, managing conversation memory, and implementing streaming output. Ideal for building complex, tool-augmented workflows.

A comprehensive workflow designed for clinical professionals to search, retrieve, and synthesize medical evidence. It allows users to query clinical literature with specialized filters (e.g., specialty, evidence level), check potential drug interactions against patient profiles, and look up the latest specialty guidelines from major health organizations (like ACC/AHA, NICE). The output provides structured citations, confidence scores, and evidence grading to support informed clinical decision-making.

Performs a full GEO audit of any website by discovering business type, crawling prioritized pages, and delegating parallel subagents to evaluate AI visibility, platform readiness, technical infrastructure, EEAT content, and schema markup, then outputs a composite GEO score with prioritized actions.

DiffDock is a cutting-edge deep learning tool leveraging diffusion models to predict the 3D binding poses of small molecule ligands to protein targets. It supports structure-based drug discovery, enabling single-complex docking, batch virtual screening, and lead optimization. Users can input protein structures (PDB) or sequences, along with diverse ligand formats (SMILES, SDF, MOL2). The tool outputs predicted poses and confidence scores, making it crucial for identifying potential drug candidates, though it does not predict binding affinity.

Automates comprehensive regression testing for all enabled cloud Large Language Model (LLM) providers. This includes verifying core connectivity, standard chat completion, structured JSON output, and Server-Sent Events (SSE) streaming capabilities. Essential for ensuring the reliability and stability of multi-cloud AI integrations in a CI/CD pipeline.

This advanced skill orchestrates a comprehensive, multi-agent review of legal contracts. It analyzes risk, compliance, missing protections, and plain-English readability simultaneously. By simulating a team of legal specialists, it aggregates findings into a single executive report, complete with a quantifiable Contract Safety Score (0-100). Ideal for founders, freelancers, or small businesses needing expert legal insights without retaining full-time counsel.

This skill guides the process of routing a complex goal through an AI's scored-memory loop using the `acc_act(runtime="solve")` function. It provides a structured workflow for deliberation, handling intermediate `brain_frame` results, and submitting continuous proposals. It emphasizes systematic reasoning and requires careful resolution of all generated frames to ensure a robust and verifiable solution.

Tamarind Bio is a cloud platform providing managed GPU access to hundreds of open-source computational biology tools. It facilitates complex tasks such as protein structure prediction (AlphaFold), de novo protein design, antibody engineering, protein-ligand docking, and molecular dynamics simulations. Users submit jobs via a unified API and receive predicted structures and biophysical scores without needing local high-performance computing resources.