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Found 1,567 Skills
Expert Python developer specializing in Python 3.11+ features, type annotations, and async programming patterns. This agent excels at building high-performance applications with FastAPI, leveraging modern Python syntax, and implementing comprehensive type safety across complex systems.
Practical Python craftsmanship guidance based on One Python Craftsman. Use when writing, refactoring, or reviewing Python code for naming, branching, data structures, functions, exceptions, loops, decorators, imports, file I/O, edge cases, and modern syntax choices. If the skills set includes friendly-python, suggest invoking it for better Python outcomes.
Guide for implementing gRPC-based key-value store services in Python. This skill should be used when building gRPC servers with protobuf definitions, implementing KV store operations (Get, Set, Delete), or troubleshooting gRPC service connectivity. Applicable to tasks involving grpcio, protobuf code generation, and background server processes.
Guide for setting up local PyPI servers to host and serve Python packages. This skill should be used when tasks involve creating a local PyPI repository, serving Python packages over HTTP, building distributable Python packages, or testing pip installations from a custom index URL.
Build applications with the Letta API — a model-agnostic, stateful API for building persistent agents with memory and long-term learning. Covers SDK patterns for Python and TypeScript. Includes 24 working code examples.
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
Use when designing error handling, retry policies, timeout behavior, or failure classification in Python. Also use when code swallows exceptions, loses error context across boundaries, has unbounded retries, silent failures, or lacks idempotency guarantees on retried writes.
Use when building or reviewing external API integrations in Python — designing client boundaries, defining outbound reliability policy, or structuring contract tests. Also use when provider SDK details leak into domain logic, outbound calls lack timeout/retry policy, or failure paths are untested.
Use when designing module boundaries, planning refactors, or reviewing architecture in Python codebases. Also use when facing tangled dependencies, god classes, deep inheritance hierarchies, unclear ownership, or risky structural changes.
Use when defining or evolving public interfaces, schema boundaries, or pydantic usage in Python. Also use when annotations are missing on public APIs, pydantic models appear everywhere instead of at trust boundaries, contract changes lack migration guidance, or Any/object types are overused across module boundaries.
Generates API documentation from code including OpenAPI specs, JSDoc, and Python docstrings. Use when documenting APIs, REST endpoints, or library functions.
Comprehensive pre-merge validation checklist for Python/React pull requests. Use before approving or merging any PR. Covers code quality checks (linting, formatting, type checking), test coverage requirements, documentation updates, migration safety, API contract compatibility, accessibility compliance, bundle size impact, and deployment readiness. Provides a systematic checklist that ensures nothing is missed before merge. Does NOT cover security review depth (use code-review-security).