Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Supports probabilistic batch correction, transfer learning, and differential expression with uncertainty. Covers advanced multimodal integration using models such as scVI, TOTALVI, and MultiVI.
Supports large scientific computing pipelines with chunked arrays, compression, and parallel I/O. Covers S3 and GCS access through fsspec and compatibility with NumPy, Dask, and Xarray.
Provides an autonomous research pipeline from a topic idea to a complete academic paper. Includes real citations, experiments, and conference-ready LaTeX output.
Guides code and architecture reviews using clean code fundamentals. Covers SOLID principles, design patterns, DRY, KISS, refactoring, and software design decisions.
Covers multi-stage builds, .NET container images, non-root users, health checks, and .dockerignore. Supports image size optimization and Docker Compose setup for local development.
Supports music creation, songwriting, lyrics generation, and audio production. Can turn supplied lyrics into songs or generate background music from a described mood or scene.
Covers MapGroup, endpoint filters, TypedResults, parameter binding, and route conventions. Supports HTTP endpoint creation and OpenAPI documentation setup.
Covers preprocessing, event and interval analysis, multimodal alignment, variability, and complexity. Emphasizes reproducible workflows and method-aware validation rather than diagnosis or device validation.
Covers semantic caching on Redis Cloud through SDK and REST search/set operations. Guides similarity thresholds, custom attribute filtering, task-specific caches, and cache-aside integration for LLM completions or RAG answers.
Supports direct use of the esm Python SDK and ESM3 or ESMC model identifiers. Covers Forge/Biohub inference clients and ESMFold2 folding workflows.
Searches for OpenClaw skills across various sources. Helps users discover available skills, locate specific functionality, and identify new skills to install.
Supports Python workflows for SAM, BAM, CRAM, VCF, BCF, FASTA, FASTQ, and tabix data. Covers pileup, coverage calculations, indexing, and CRAM reference handling.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name