prompt-builder
Build complete agent prompts deterministically via Python script. Use BEFORE spawning any BAZINGA agent (Developer, QA, Tech Lead, PM, etc.).
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Build complete agent prompts deterministically via Python script. Use BEFORE spawning any BAZINGA agent (Developer, QA, Tech Lead, PM, etc.).
python-controlを使用して、メカニカルシステムの状態空間モデルから伝達関数(Bode Plot)を計算・表示する
Read and analyze Inspect AI evaluation log files using the Python API. Extract samples, messages, events, and metrics from .eval files.
This skill should be used when detecting and fixing color contrast issues in the codebase. It finds dark text on dark backgrounds and light text on light backgrounds, then provides fixes to ensure proper readab...
코드 리뷰 전문 skill. TypeScript, JavaScript, Python, Swift, Kotlin, Go 지원. 정적 분석, 베스트 프랙티스 검사, 보안 스캔, 리뷰 체크리스트 생성. 사용 시기: (1) PR 리뷰 시 (2) 코드 품질 피드백 시 (3) 보안 취약점...
Guide for developing the API service using Python, FastAPI, Pydantic, and Docker. Use this when creating or modifying API endpoints, models, routers, or backend logic.
Provides guidance and explanations on Python code structure, organization, and architectural patterns tailored for students and beginners.
how to run python files and mangage dependencies using UV package manager (pip replacement)
High-performance C development for data-intensive systems, with explicit emphasis on time-indexed / log-structured in-memory engines (e.g., Timelog-class designs). Use when building advanced data structures, al...
Senior Python developer for Python 3.11+. Use for type-safe, async, production-ready code.
Python tooling conventions for this organization. Use when working with Python projects, fixing linting issues, or managing dependencies.
Safely install a Python package, verify it imports correctly, and pin it to requirements.txt
Asynchronous programming patterns for Python, JavaScript/TypeScript, and other languages. Auto-triggers when implementing concurrent code, handling promises, or optimizing I/O operations.
Use when profiling Python code, optimizing performance, implementing async patterns, or working with concurrent I/O - covers cProfile, line_profiler, asyncio patterns, and multiprocessing for CPU-bound tasks (p...
Python >=3.11 performance optimization guidelines. This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data...
Use when writing pytest tests, creating fixtures, mocking dependencies, or testing async code - provides patterns that verify actual behavior with proper fixtures and parametrization; prevents testing mocks ins...
Use when setting up Python projects, managing dependencies with uv, configuring pyproject.toml, creating project structure, or publishing packages - provides modern Python 3.12+ tooling patterns with uv package...
Run the CPython regression test suite in this repo via scripts/run_cpython_tests.sh with parallel execution, enforce a per-test timeout, capture output to cpython_full_test_run.log, and summarize failures from...
Use when you need a detailed execution trace of a Python script using sys.monitoring, including logging every operation with include/exclude event controls.
Use when you need to inspect detailed execution flow of a Python program, stepping through functions and inspecting variable contents with pdb. Triggers include requests to debug Python scripts, trace execution...
Summarize CPython test failures from cpython_full_test_run.log (and cpython_full_test_run_summary.txt if present), compute passed/total counts for test files and test cases, and group failures by likely root ca...
Generate a tiny non-sensitive WAV file using only the Python standard library. Use for deterministic smoke tests without committing real user audio.
Run analyzer MCP tools (Ruff + optional dead-code scan) as a quality gate before QA/UAT/release.
Run Python pytest suites and capture reproducible evidence (command, environment, output) into agent-output artifacts. Use for QA verification, debugging, and pre-release confidence.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.