🎯Skills202
A library of 199 bioinformatics skills for AI coding agents, covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over the baseline.
The largest open-source skill library for scientific AI agents, with 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on BixBench, the highest among all tested systems.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on the BixBench benchmark, up from a 65% baseline.
The largest open-source skill library for scientific AI agents, with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a library of 199 scientific skills for Claude Code spanning genomics, proteomics, drug discovery, scientific writing, and data visualization, with proven 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, boosting BixBench benchmark accuracy from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering single-cell analysis, genomics, proteomics, drug discovery, and more, which achieved 92% accuracy on the BixBench benchmark.
A bioinformatics skill from SciAgent-Skills for protein-protein interaction analysis using the STRING database, part of a 199-skill scientific computing library that boosted BixBench accuracy to 92%.
The largest open-source scientific skill library for AI agents, with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and more. Achieved 92.0% accuracy on BixBench, a +26.7 point improvement over baseline Claude Code.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on BixBench, boosting Claude Code baseline from 65% without fine-tuning.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for scientific AI agents covering computational biology, cheminformatics, and biostatistics, which boosted BixBench benchmark accuracy from 65% to 92%.
A scientific visualization skill from SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering data visualization, cell biology, and scientific computing across 11 categories.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering genomics, proteomics, drug discovery, biostatistics, and scientific computing, which achieved 92% accuracy on the BixBench benchmark.
A bioinformatics skill from SciAgent-Skills that provides domain knowledge for working with the Reactome pathway database, part of a 199-skill library for computational biology, systems biology, and multi-omics analysis.
The largest open-source scientific skill library for AI agents, with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and biostatistics. Achieved 92% accuracy on the BixBench benchmark, a 26.7 percentage point improvement over baseline.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% on BixBench.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, boosting BixBench benchmark accuracy from 65% to 92%.
A Claude Code skill from the SciAgent-Skills collection that provides guidance on KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis, enabling biological pathway mapping, enrichment analysis, and metabolic network exploration.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents that boosted BixBench accuracy from 65% to 92%. This skill provides guidance for scientific manuscript writing, peer review, LaTeX posters, slides, and figure preparation.
SciAgent-Skills equips AI coding agents with 199 bioinformatics skills for computational biology, including RNA-seq, single-cell analysis, genomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for Claude Code that equips AI agents with domain-specific knowledge for computational biology, bioinformatics, and biostatistics. Boosted BixBench benchmark accuracy from 65% to 92%.
A skill from SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, which boosted BixBench scores from 65% to 92%.
A collection of 199 bioinformatics skills for AI coding agents, covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, up from a 65% baseline.
Part of SciAgent-Skills, a 199-skill bioinformatics library that boosted BixBench accuracy from 65% to 92%, covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and scientific computing for Claude Code.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents that provides domain-specific knowledge for computational biology, bioinformatics, and biostatistics, boosting BixBench accuracy from 65% to 92%.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery for Claude Code. Achieved 92% accuracy on the BixBench bioinformatics benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on BixBench.
Part of SciAgent-Skills, the largest open-source scientific skill library with 199 bioinformatics skills for AI agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on BixBench.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Boosted BixBench scores from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering computational biology, cheminformatics, and biostatistics. Each skill provides runnable code examples, key parameters, troubleshooting guides, and best practices.
A bioinformatics skill from SciAgent-Skills, a library of 199 scientific computing skills for Claude Code that boosted BixBench accuracy from 65% to 92%, covering genomics, proteomics, drug discovery, and more.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills. Listed under the Data Visualization category, which covers tools like Plotly and Seaborn for scientific computing.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% on BixBench.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering computational biology, cheminformatics, and biostatistics. Improved BixBench benchmark accuracy from 65% to 92% without fine-tuning.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents. This skill provides guidance for computational chemistry and drug discovery using DeepChem, within the structural biology domain alongside RDKit, AutoDock Vina, ChEMBL, and PDB.
Part of SciAgent-Skills, a library of 199 bioinformatics skills that equips AI coding agents with domain knowledge for computational biology, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills. Covers computational biology, cheminformatics, and biostatistics, boosting BixBench accuracy by over 26 percentage points.
The largest open-source skill library for scientific AI agents, with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on BixBench.
Skill
A drug discovery and structural biology skill from SciAgent-Skills, a library of 199 bioinformatics skills that includes 53 database connectors and 26 skills for structural biology and drug discovery workflows.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and biostatistics, which boosted BixBench scores from 65% to 92%.
A library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, boosting performance from a 65% baseline.
A bioinformatics agent skill from SciAgent-Skills, a 199-skill library that boosted BixBench accuracy from 65% to 92% by equipping Claude Code with domain-specific knowledge for computational biology, covering RNA-seq, single-cell analysis, proteomics, and drug discovery.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on the BixBench benchmark, a 26.7 percentage point improvement over baseline.
Part of SciAgent-Skills, a library of 199 bioinformatics skills that equips AI coding agents with domain knowledge for computational biology, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over baseline.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source scientific skill library for AI coding agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and more. It boosted BixBench scores from 65% to 92%, equipping Claude Code with domain-specific knowledge for computational biology without fine-tuning.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92.0% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering genomics, proteomics, drug discovery, and biostatistics, which boosted BixBench accuracy from 65% to 92%.
SciAgent-Skills is the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. It boosted BixBench accuracy from 65% to 92%.
A library of 199 bioinformatics skills for Claude Code that covers RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a 199-skill bioinformatics library for Claude Code covering structural biology, drug discovery, and molecular docking workflows. The library improved BixBench benchmark scores from 65% to 92%.
Part of SciAgent-Skills, a bioinformatics skill library providing 199 skills for AI coding agents. Designed for Claude Code, it provides domain-specific knowledge for RNA-seq, single-cell analysis, drug discovery, and protein structure prediction without fine-tuning.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery that boosted BixBench accuracy from 65% to 92%.
Part of a Laravel and Vue skills collection for AI coding agents, installable via the universal skills CLI. Includes optional Vue-related skills for Nuxt, VueUse, and Reka UI, with support for OpenCode agent integration.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, an open-source library providing 199 scientific skills for AI agents with a focus on genomics, proteomics, drug discovery, and scientific computing. Boosted BixBench benchmark performance from 65% to 92% when used with Claude Code.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, offering 199 bioinformatics skills for Claude Code that span RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, with 92% accuracy on BixBench.
Part of SciAgent-Skills, the largest open-source scientific skill library with 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on BixBench.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery for Claude Code. Achieved 92% accuracy on the BixBench bioinformatics benchmark.
A skill from SciAgent-Skills, which provides 199 bioinformatics skills for Claude Code covering computational biology, cheminformatics, and biostatistics. The skill library boosted BixBench benchmark performance from 65% to 92.0% without requiring model fine-tuning.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills. Belongs to the Scientific Writing category covering manuscript writing, peer review, LaTeX posters, slides, and figure guides.
Part of SciAgent-Skills, providing 199 ready-to-use scientific skills for AI coding agents across genomics, proteomics, drug discovery, and scientific writing. Each skill is a self-contained SKILL.md file with runnable code examples and best practices.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills, equipping Claude Code with domain knowledge for computational biology, bioinformatics, cheminformatics, and biostatistics. Achieved 92.0% on the BixBench benchmark.
Part of SciAgent-Skills, a 199-skill bioinformatics library for Claude Code covering systems biology and multi-omics integration using tools like COBRApy, LaminDB, Reactome, and STRING. The library improved BixBench benchmark scores from 65% to 92%.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark (up from 65% baseline).
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills. Covers computational biology topics including genomics, structural biology, drug discovery, and molecular biology with practical code examples and best practices.
Part of SciAgent-Skills, a 199-skill bioinformatics collection for Claude Code that includes LaTeX poster and slide creation alongside skills for RNA-seq, genomics, proteomics, and drug discovery.
The largest open-source skill library for scientific AI agents, with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over baseline Claude Code.
A collection of 199 scientific computing skills that turn AI coding assistants into domain experts, covering areas like machine learning, data analysis, and scientific workflows with a 92% BixBench score.
Part of a comprehensive Unity Claude Code plugin providing 35 skills covering the entire Unity Game Engine documentation, based on Unity 6.3 LTS. Contains 95 files with over 44,500 lines of actionable development guidance, patterns, and API references.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for Claude Code that covers genomics, proteomics, drug discovery, and more. The collection boosted BixBench benchmark accuracy from 65% to 92% by providing domain-specific scientific knowledge.
Skill
SciAgent-Skills is a collection of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, boosting BixBench scores from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents. This skill covers mass spectrometry analysis using PyOpenMS, within the proteomics and protein engineering domain alongside ESM, UniProt, matchms, and HMDB tools.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, which boosted BixBench scores from 65% to 92%.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. The collection achieved 92% accuracy on the BixBench benchmark.
The largest open-source scientific skill library with 199 bioinformatics skills for Claude Code, covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on BixBench, a +26.7 point improvement over baseline.
Part of SciAgent-Skills, a library of 199 bioinformatics skills that equips AI coding agents with domain-specific knowledge for computational biology, covering genomics, cell biology, proteomics, drug discovery, and scientific computing.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, which boosted BixBench accuracy from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills, this skill falls under the scientific writing category covering peer review methodology, manuscript evaluation, and structured feedback for scientific publications.
Part of SciAgent-Skills, equipping Claude Code with domain-specific knowledge for computational biology and bioinformatics through 199 self-contained skills. Covers RNA-seq, single-cell analysis, drug discovery, and scientific computing with no model fine-tuning needed.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92.0% on BixBench.
A collection of 199 bioinformatics skills for AI coding agents, covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over baseline Claude Code.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery for Claude Code. Achieved 92% accuracy on the BixBench bioinformatics benchmark.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark with a +26.7 percentage point improvement over baseline.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for Claude Code covering genomics, proteomics, drug discovery, and biostatistics that boosted BixBench accuracy from 65% to 92%.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Boosted BixBench scores from 65% to 92%.
Skill
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 26.7 percentage point improvement over baseline Claude Code.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% on the BixBench benchmark, up from 65% without skills.
Part of SciAgent-Skills, the largest open-source scientific skill library with 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench bioinformatics benchmark.
199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, boosting BixBench benchmark accuracy from 65% to 92% without fine-tuning.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% on the BixBench benchmark, up from 65% without skills.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills. Covers genomics, proteomics, drug discovery, biostatistics, and scientific computing, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills for Claude Code covering genomics, proteomics, drug discovery, and scientific computing. Each skill is a self-contained SKILL.md with runnable code examples and best practices.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on BixBench-Verified-50, boosting Claude Code's baseline from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over baseline.
A bioinformatics skill from the SciAgent-Skills library, which provides 199 scientific skills for AI coding agents covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. The library achieved 92.0% accuracy on the BixBench benchmark, a 26.7 percentage point improvement over baseline.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved a 92% score on the BixBench benchmark, up from a 65% baseline.
A bioinformatics skill from SciAgent-Skills, a library of 199 scientific skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery that boosted BixBench accuracy from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents that covers genomics, proteomics, drug discovery, biostatistics, and scientific computing. Boosted BixBench benchmark accuracy from 65% to 92% with no fine-tuning required.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for AI coding agents covering genomics, proteomics, drug discovery, and more, which boosted BixBench accuracy from 65% to 92%.
A Claude Code skill from the SciAgent-Skills collection that provides guidelines for creating figures meeting PNAS (Proceedings of the National Academy of Sciences) publication standards, covering formatting, sizing, and submission requirements.
Part of SciAgent-Skills, a library of 199 scientific computing and bioinformatics skills for Claude Code that achieved 92% accuracy on BixBench, covering RNA-seq, single-cell analysis, proteomics, and computational biology.
A specification-driven document-flow framework for AI-assisted software development that defines an 8-layer SDD flow (BRD through Code), with both a Hermes MCP server and a Claude Code plugin implementation sharing a common conformance test suite.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills that turns AI coding agents into life sciences experts, covering scientific computing, genomics, and drug discovery with 92% accuracy on BixBench.
The largest open-source bioinformatics skill library for AI agents, with 199 skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% on the BixBench benchmark, up from a 65% baseline.
A Claude Code skill from the SciAgent-Skills collection (199 scientific skills, BixBench 92%) that provides guidance on creating publication-quality scientific figures, covering data visualization best practices, formatting, and journal-specific requirements.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92.0% accuracy on BixBench, up from 65% baseline.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and more. Achieved 92.0% accuracy on BixBench-Verified-50.
Part of the SciAgent-Skills collection, offering 199 plug-and-play bioinformatics skills for AI coding agents. Covers RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and other life sciences domains with no fine-tuning required.
The largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, up from 65% baseline.
A Claude Code plugin that lets you get a second opinion from GitHub Copilot during development. Part of a plugin collection that integrates with multiple AI coding assistants including Claude, Codex, and Gemini.
Part of SciAgent-Skills, the largest open-source scientific skill library for AI coding agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source scientific skill library for AI agents with 199 skills covering genomics, proteomics, drug discovery, biostatistics, and scientific computing, boosting BixBench accuracy from 65% to 92%.
Part of SciAgent-Skills, a collection of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery that boosted BixBench scores from 65% to 92%.
Part of SciAgent-Skills, a library of 199 bioinformatics skills for scientific AI agents covering structural biology, drug discovery, cheminformatics, and more. The collection achieved 92% accuracy on the BixBench benchmark.
A genomics and bioinformatics skill from SciAgent-Skills, a library of 199 scientific computing skills for AI coding agents that boosted BixBench benchmark accuracy from 65% to 92%, covering areas like RNA-seq, single-cell analysis, and proteomics.
The largest open-source scientific skill library for AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery. Achieved 92% accuracy on the BixBench benchmark, a 27-point improvement over the baseline.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents with 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% on the BixBench benchmark.
Part of SciAgent-Skills, the largest open-source skill library for scientific AI agents, providing 199 bioinformatics skills covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, achieving 92% accuracy on the BixBench benchmark.
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and biostatistics, achieving 92% accuracy on BixBench.
Part of the SciAgent-Skills library with 199 bioinformatics skills for Claude Code, covering RNA-seq, single-cell analysis, genomics, proteomics, and drug discovery, which boosted BixBench accuracy from 65% to 92%.
Skill
A library of 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and more, achieving 92% accuracy on the BixBench benchmark (up from 65% baseline).
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