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Found 33 Skills
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.
Auxiliary development skill for Tongda Xin quantitative platform (TdxQuant). Use this skill when users mention "Tongda Xin", "TDX", "TdxQuant", "quantitative trading" or ask about the usage of the `tqcenter` module. It can help with environment setup, API calling, market data acquisition and trading strategy implementation.
Retrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution time, query traces, or debug failed traces. Triggers on "get trace", "search traces", "find failed traces", "filter traces by", "traces slower than", "query MLflow traces".
Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment
Expert skill for using OpenViking, the open-source context database for AI Agents that manages memory, resources, and skills via a filesystem paradigm.
Comprehensive skill for Adobe Substance 3D Painter texturing and material creation workflow. Use this skill when creating PBR materials, exporting textures for web/game engines, optimizing 3D assets for real-time rendering, or automating texture workflows. Triggers on tasks involving Substance 3D Painter, PBR texturing, material creation, texture export for Three.js, Babylon.js, Unity, Unreal, glTF optimization, or Python API automation. Creates optimized textures for threejs-webgl, react-three-fiber, and babylonjs-engine materials.
Stateful LLDB debugging via LLDB Python API
One-click model liberation toolkit for removing refusal behaviors from LLMs via surgical abliteration techniques
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when Claude needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic coordinates with projections, (4) Reduce large datasets using block averaging, (5) Remove polynomial trends from spatial data, (6) Cross-validate gridding parameters, (7) Create processing pipelines with Chain, (8) Grid vector data like GPS velocities.
Solve LP, MILP, QP (beta) with cuOpt Python API — linear/quadratic objectives, integer variables, scheduling, portfolio, least squares.
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.