Search Skills

Provides experimental guidance for SPR and BLI binding kinetics studies, including troubleshooting, data interpretation, and platform selection.

End-to-end protein binder design with AlphaFold2 validation, enabling joint backbone and sequence optimization for high experimental success.

Ranks protein binder designs using ipSAE for experimental testing, prediction, and comparison of structure predictions.

Guides selection of protein binder design tools (e.g., BoltzGen, BindCraft, RFdiffusion) by analyzing trade-offs and target-specific requirements for scientific campaigns.

Optimizes protein sequences for solubility and high-yield E. coli expression, reducing aggregation and inclusion body formation.

Retrieves protein sequences, annotations, domain boundaries, homologs, and variants from UniProt for scientific research and analysis.

Fetches and analyzes protein structures from RCSB PDB, enabling tasks like downloading by ID, searching similar structures, and extracting chains for scientific research.

Generates all-atom protein structures using a diffusion model, enabling side-chain aware design, ligand binding, and precise geometries via YAML configuration.

Initializes protein design tool environment, resolving common setup issues like missing files, authentication errors, and command not found for new users.

Provides protein sequence embeddings and scoring using ESM2 for PLL computation, clustering, and variant effect prediction.

Offers expert guidance for optimizing cell-free protein synthesis (CFPS) experiments, including troubleshooting low yield and DNA template design for challenging protein expression.

Provides end-to-end guidance for protein design projects, including tool selection, QC thresholds, and resource planning.

AI-driven protein sequence design for ligand binding, active site optimization, and cofactor interactions.

Predicts molecular structures including protein-protein and protein-ligand complexes using Chai-1, an AI foundation model, as an alternative to AlphaFold2.

Predicts protein complex and protein-ligand structures using open-source Boltz AI models as an alternative to AlphaFold2.

Enables structural similarity searches in PDB/AFDB databases using Foldseek for homology detection, clustering, and remote homolog identification in protein structures.

Provides research-backed quality control metrics and thresholds for protein design evaluation, including binding, expression, and structural metrics.

Provides comprehensive code review analyzing security, performance, and maintainability to identify defects and enhance code quality.

Guides users through multi-step plugin workflows, demonstrating efficient structuring and execution of sequential tasks.

Provides official documentation for Claude Code CLI, plugins, hooks, MCP servers, skills, and configuration.

Provides streamlined workflows for developing, testing, and maintaining plugins within the Claude Code ecosystem.

Provides expert UI/UX guidance for accessible interfaces, covering color, typography, layout, and visual decisions while consulting users before implementation.

Generates distinctive, production-grade frontend interfaces with high design quality, avoiding generic AI aesthetics for web components, pages, and applications.

Switches between quality, balanced, and budget model profiles for kata agents to optimize AI performance and cost.