Check if upstream Apache DataFusion features (functions, DataFrame ops, SessionContext methods, FFI types) are exposed in this Python project. Use when adding missing functions, auditing API coverage, or ensuring parity with upstream.
Audit and improve datafusion-python functions to accept native Python types (int, float, str, bool) instead of requiring explicit lit() or col() wrapping. Analyzes function signatures, checks upstream Rust implementations for type constraints, and applies the appropriate coercion pattern.
Use when the user is writing datafusion-python (Apache DataFusion Python bindings) DataFrame or SQL code. Covers imports, data loading, DataFrame operations, expression building, SQL-to-DataFrame mappings, idiomatic patterns, and common pitfalls.
Modernize FlyDSL kernels: replace raw MLIR dialects (arith, scf, vector, llvm, memref, math), ArithValue, redundant fx. wrapping, fx.Index, bufferops, SmemPtr/SmemAllocator, copyatomcall/mmaatomcall (loop or single atom), and raw rocdl.mfma with the current fx. surface (fx types, Python control flow, makebuffertensor…
Kolo is a text-based Python debugger for AI agents. Capture every executed function, return value, local variable, HTTP request, and SQL query into greppable trace files.
Kolo is a text-based Python debugger that captures every executed function, return value, local variable, HTTP request, and SQL query into greppable trace files. Use this skill for tricky debugging challenges, to verify that code behaves as expected at runtime, and to see the real data and values passing through the…
A generic workflow for self-starting TouchDesigner via computer-use (or an already-running instance), loading mcpwebserverbase.tox, and verifying any TD-side Python change (td/modules/) directly from the Textport — reading back real TD runtime values and reconciling them. Use after changing TD-side code in the…
Builds bidirectional Streamlit Custom Components v2 (CCv2) using st.components.v2.component. Use when authoring inline HTML/CSS/JS components or packaged components (manifest assetdir, js/css globs), wiring state/trigger callbacks, theming via --st- CSS variables, or bundling with Vite / component-template v2.
Simplifies and refines Python code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise.
Specialized execution agent for OmicVerse-based analysis. Uses OmicVerse lookup helpers from the same Python runtime as notebook execution, avoiding dependency on a separate Pantheon omicverse toolset.
Write code that calls the installed nvMolKit Python API for GPU-accelerated, batched RDKit-style operations - Morgan fingerprints, Tanimoto/cosine similarity, ETKDG conformer embedding, MMFF/UFF optimization, TFD, conformer RMSD, Butina clustering, and substructure search. Use when the user is importing nvmolkit.…
A conversion guide for moving Python trading strategies from miniQMT, an external trading setup, into the Python environment built into bigQMT, a trading client. It covers code changes, compatibility checks, deployment, and live-trading verification.
Drive a live marimo notebook as a workspace: run Python in the same kernel the user does, inspect live notebook state, and commit durable notebook changes. Use when the user wants to start a marimo notebook or pair on an active marimo session.
Creates Python projects with proper structure, virtual environments, and dependency management. Use when users request to create a new Python project, set up a Python development environment, or initialize a Python application with standard tooling.
Use when modifying, testing, documenting, or reviewing the Vulners Python SDK. Covers the v4 architecture (typed sync/async clients, resource namespaces, bulletin model hierarchy, unasync codegen), the preserved legacy v3 surface, uv-based tooling, the 100% branch-coverage gate, safe API-key handling, and defensive…
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
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At most 3 mods per repository are shown here — the rest are on their repository pages: