Dataset Curator
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Curate and clean training datasets for high-quality machine learning
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Best practices for scikit-learn machine learning, model development, evaluation, and deployment in Python
step-functions
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AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or...
Build resumable state-machine workflows with checkpoint patterns, progress preservation, and automatic recovery for complex multi-phase operations that need to survive interruptions, timeouts, and...
Patterns for OrbStack Linux VMs and Docker on macOS. Covers orbctl/orb commands, machine lifecycle, cloud-init, networking, file sharing, and SSH access. Must use when working with OrbStack,...
Sentiment Analysis
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Classify text sentiment using NLP techniques, lexicon-based analysis, and machine learning for opinion mining, brand monitoring, and customer feedback analysis
transition
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Define how state changes over time through rules, triggers, and effects. Use when modeling state machines, defining workflows, specifying event handlers, or documenting system dynamics.
ssh
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Establish and manage SSH connections to remote machines, including key generation, configuration, and file transfers. Use when connecting to remote servers, executing remote commands, or...
data-scientist
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Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.
metaplex
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Complete Metaplex Protocol guide for Solana NFTs and digital assets. Covers Core (next-gen NFTs), Token Metadata, Bubblegum (compressed NFTs), Candy Machine, Genesis (token launches), MPL-Hybrid,...
scikit-learn
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Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model...
scikit-learn
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Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model...
scikit-learn
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Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model...
jax-best-practices
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Expert in JAX for high-performance numerical computing and machine learning
auth-implementation
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Expert guidance for implementing secure authentication systems including OAuth 2.0, SAML, OIDC, JWT, passwordless authentication, passkeys, and biometrics. Covers protocol selection, security best...
dask
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Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing,...
gtars
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High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML...
gtars
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High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML...
FOLLOW THE STATE MACHINE IN SKILL.MD. When user says 'continue': (1) FIRST: Run pwd, (2) Announce STATE: CHECK_STATUS, (3) Read .claude/session.md to check Status field, (4) Route based on Status....
gtars
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High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML...