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data-engineering
ML data engineering covering data pipelines, data quality, collection strategies, storage, and versioning for machine learning systems.
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Research AI Skills
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thinking-in-omega-modes
Applies 7 systematic thinking modes for breakthrough problem-solving and 10x improvements. Use when tackling complex problems, seeking transformative insights, or escaping conventional thinking traps.
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GitHub
caching-strategies
Multi-layer caching with Redis, CDN, and browser caching for optimal application performance
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GitHub
efficient-ai
Efficient AI techniques including model compression, quantization, pruning, knowledge distillation, and hardware-aware optimization for production systems.
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GitHub
testingmutation-testing
Mutation testing with Stryker to verify test quality by introducing code mutations and measuring detection rates
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GitHub
ml-systems
Machine Learning Systems - comprehensive knowledge for building production ML systems from data engineering through deployment and operations. Based on Harvard ML Systems course and Designing ML Systems by Chip...
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GitHub
python
Python development with type hints, async patterns, testing, and modern best practices
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GitHub
writing-plans
AI agent creates structured implementation plans with task breakdown, dependency mapping, risk assessment, and file-level detail. Use when planning features, projects, or complex implementations.
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GitHub
processing-media
Processes audio and video with ffmpeg including transcoding, streaming, and batch operations. Use when building video pipelines, converting formats, generating thumbnails, or implementing HLS/DASH streaming.
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GitHub
testingcomprehensive-testing
Comprehensive 4D testing methodology covering Accuracy, Performance, Security, and Accessibility for production-ready quality assurance
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GitHub
training-data
Training data management including labeling strategies, data augmentation, handling imbalanced data, and data splitting best practices.
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GitHub
advanced-ui-design
Agency-grade interface design with systematic aesthetic framework (BEAUTIFUL → RIGHT → SATISFYING → PEAK)
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GitHub
testing-with-pytest
Claude writes comprehensive Python tests using pytest. Use when writing unit tests, creating fixtures, parametrizing tests, mocking dependencies, testing async code, or setting up CI test pipelines.
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GitHub
deep-learning-primer
Deep learning foundations including neural network basics, backpropagation, optimization, regularization, and training best practices.
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GitHub
building-3d-graphics
Claude builds immersive 3D web experiences with Three.js and React Three Fiber. Use when creating WebGL scenes, 3D animations, shaders, or physics simulations.
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GitHub
test-enforcement
The agent enforces mandatory test completion before any task or feature can be marked as done, ensuring code quality through strict validation gates and evidence-based completion criteria.
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GitHub
robust-ai
Building robust AI systems including model monitoring, drift detection, reliability engineering, and failure handling for production ML.
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GitHub
rails
Enterprise Ruby on Rails development with Active Record, API mode, testing, and production patterns
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GitHub
infographic-creator
Create beautiful infographics based on the given text content. Use this when users request creating infographics.
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GitHub
deck-creator
Create, update, and translate Dify X Reveal.js slide decks in this repo. Use when asked to draft slides, extract outlines, or maintain bilingual CN/EN parity for the ctrip/paypal/pupu/milvus/aispeech/dentsply/o...
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GitHub
doppler
Fetch secrets from Doppler for API keys and credentials.
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GitHub
bump-release
Execute automated release workflow for Rust projects using Conventional Emoji Commits. Analyze commits since last release, determine semantic version bump (MAJOR/MINOR/PATCH), update Cargo.toml, generate change...
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GitHub
test-runner-worktree
Run Rust cargo tests properly in git worktrees with environment variable sourcing. Use when cargo test fails, when seeing authentication errors, when test results differ between runs, or before running pre-comm...
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GitHub
git-worktrees
Manage git worktrees for parallel feature development following Langstar's issue-driven workflow. Create worktrees with correct target branches based on issue hierarchy, handle cleanup after PR merge, and maint...
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The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.