> browse/registry

> pandas

Assists with loading, cleaning, transforming, and analyzing tabular data using pandas. Use when importing CSV/Excel/SQL data, handling missing values, performing groupby aggregations, merging datasets, working with time series, or building analysis-ready datasets. Trigger words: pandas, dataframe, csv, groupby, merge, time series, data cleaning.

> onnx

Open Neural Network Exchange format for model interoperability across frameworks. Export models from PyTorch, TensorFlow, and other frameworks to ONNX, optimize with ONNX Runtime, and deploy for cross-platform inference on CPU, GPU, and edge devices.

> kamal

Deploy web applications to any server with Kamal — zero-downtime Docker deployments without Kubernetes. Use when someone asks to "deploy to a VPS", "deploy without Kubernetes", "Kamal deploy", "simple Docker deployment", "deploy Rails/Node/Python to a server", "zero-downtime deployment to bare metal", or "replace Heroku with a VPS". Covers Docker-based deployment, zero downtime with Traefik, multi-server, secrets, and accessory services.

> deepeval

Expert guidance for DeepEval, the open-source framework for unit testing LLM applications. Helps developers write test cases, define custom metrics, and integrate LLM quality checks into CI/CD pipelines using a pytest-like interface.

> renovate

Assists with automating dependency updates across JavaScript, Python, Docker, Go, Rust, Terraform, and 50+ ecosystems using Renovate. Use when configuring update strategies, automerge policies, grouping rules, or scheduling to keep dependencies current. Trigger words: renovate, dependency updates, automerge, package rules, dependency management.

> django

Django is a batteries-included Python web framework that follows the model-template-view pattern. It provides an ORM, admin interface, authentication, and everything needed to build full-featured web applications rapidly and securely.

> locust

When the user wants to perform load testing using Python with Locust's distributed architecture and real-time web UI. Also use when the user mentions "locust," "Python load testing," "distributed load test," "locust web UI," or "locustfile." For JavaScript-based load testing, see k6 or artillery.

> aws-lambda

You are an expert in AWS Lambda, Amazon's serverless compute service. You help developers build event-driven applications using Lambda functions triggered by API Gateway, S3 events, SQS queues, DynamoDB streams, and scheduled events — with support for Node.js, Python, Go, Rust, Java, and container images, automatic scaling from zero to thousands of concurrent executions, and pay-per-invocation pricing.

> fastapi

FastAPI is a modern, high-performance Python web framework for building APIs. It leverages Python type hints and Pydantic for automatic validation, serialization, and OpenAPI documentation generation with async/await support out of the box.

> apache-arrow

Expert guidance for Apache Arrow, the cross-language columnar memory format for analytics workloads. Helps developers use Arrow for high-performance data interchange between systems, zero-copy reads, and efficient columnar processing in Python (PyArrow) and JavaScript (Arrow JS).

> celery

Run background tasks in Python with Celery. Use when a user asks to process tasks asynchronously, schedule periodic jobs, run background workers, build task queues in Python, or offload heavy processing from web requests.

> meilisearch

Add fast, typo-tolerant full-text search with Meilisearch. Use when a user asks to add search to an app, implement full-text search, set up a search engine, replace Elasticsearch with something simpler, add autocomplete or instant search, build a product catalog search, index documents for search, configure search relevancy, add faceted filtering, or deploy a self-hosted search engine. Covers indexing, querying, facets, filtering, sorting, multi-tenancy, and integration with Node.js, Python, and

> jupyter

Assists with interactive data analysis, visualization, and reproducible research using Jupyter notebooks. Use when building notebooks that combine code with rich output, managing kernels, converting to reports, or parameterizing notebooks for batch execution. Trigger words: jupyter, notebook, jupyterlab, ipynb, nbconvert, papermill.

> outlines

You are an expert in Outlines, the Python library for reliable structured text generation with LLMs. You help developers generate guaranteed-valid JSON, regex-matching text, and grammar-constrained output from open-source models — using finite state machine guided generation that constrains the token sampling process to produce only valid output on the first try.

> blender-animation

Animate 3D objects and characters in Blender with Python. Use when the user wants to keyframe properties, create armatures and rigs, set up IK/FK chains, animate shape keys for facial animation, edit F-Curves, use the NLA editor to blend actions, add drivers for expression-based animation, or script any animation workflow in Blender.

> mojo

Expert guidance for Mojo, the programming language by Modular that combines Python's usability with C-level performance. Helps developers write high-performance AI/ML code, optimize numerical computations with SIMD and parallelism, and gradually port Python code to Mojo for orders-of-magnitude speedups.

> opencv

You are an expert in OpenCV (Open Source Computer Vision Library), the most popular library for real-time computer vision. You help developers build image processing pipelines, object detection systems, video analysis tools, augmented reality, and document processing using OpenCV's 2,500+ algorithms for image manipulation, feature detection, camera calibration, 3D reconstruction, and DNN inference — in Python, C++, or JavaScript.

> polars

Polars is a blazingly fast DataFrame library written in Rust with a Python API. Learn eager and lazy evaluation, expressions, groupby, joins, and how Polars outperforms pandas for large datasets through parallel execution.

> poetry

Manage Python projects with Poetry. Use when a user asks to manage Python dependencies, create virtual environments, publish packages to PyPI, handle dependency resolution, or set up a Python project structure.

> dagger

Write CI/CD pipelines as code with Dagger — portable, cacheable, container-based pipelines that run locally and in any CI system. Use when someone asks to "write CI pipeline in TypeScript", "portable CI/CD", "run GitHub Actions locally", "Dagger pipeline", "CI as code", "containerized build pipeline", or "test my CI locally before pushing". Covers Dagger SDK (TypeScript/Python), pipeline composition, caching, secrets, and multi-stage builds.