按技能名称、说明或 GitHub 作者匹配的结果。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or...
Apply Google Style documentation standards to Python, Go, and Terraform code. Use when writing or reviewing code that needs docstrings/comments, when asked to "document this code", "add docstrings", "follow Goo...
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame...
This skill provides comprehensive guidance for SAP Business Application Studio (BAS), the cloud-based IDE on SAP BTP built on Code-OSS. Use when setting up BAS subscriptions, creating dev spaces, connecting to...
Develops data processing pipelines, integrations, and machine learning scenarios in SAP Data Intelligence Cloud. Use when building graphs/pipelines with operators, integrating ABAP/S4HANA systems, creating repl...
Upgrade Cloud Composer (Apache Airflow) to a new version. Use when the user asks to upgrade, update, or bump Airflow, Cloud Composer, or Airflow dependencies to a new version. Handles updating terraform config...
Web shell samples for detection and analysis: PHP, ASP, ASPX, JSP, Python, Perl shells. Use for security research and detection system testing.
Structural code search and refactoring using AST patterns. Use when searching for code patterns (not text), finding deprecated patterns, or systematic refactoring. Supports Nextflow, JavaScript, Python, and mor...
Advanced python-docx patterns for nested tables, complex cells, and content extraction beyond .text property. Techniques for forms, checklists, and complex layouts.
Advanced python-docx patterns for handling nested tables, complex cell structures, and content extraction beyond basic .text property. Complements the official docx skill with specialized techniques for forms,...
Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment
Comprehensive FastAPI skill for building modern Python web APIs with focus on customer support systems, ticket management, real-time chat, and backend operations
Python testing with pytest covering fixtures, parametrization, mocking, and test organization for reliable test suites
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing s...
Write self-installing autocontained Python scripts using uv and PEP 723
Work with Python (`uv` instead of `python`, modern type syntax, linting, formatting, etc.) properly!
A development process for Python applications that uses TDD to iterate on a new project based around uv. Use when Claude needs to create a new Python project, write Python code with tests, or work on Python dev...
Migrate Python projects from setup.py/setup.cfg to pyproject.toml for use with uv. Use when upgrading legacy Python packaging, converting setup.py to modern pyproject.toml format, setting up dependency groups f...
This skill should be used when editing Python code in the erk codebase. Use when writing, reviewing, or refactoring Python to ensure adherence to LBYL exception handling patterns, Python 3.13+ type syntax (list...
Python development best practices including PEP 8 style guidelines, type hints, docstring conventions, and common patterns. Use when writing or modifying Python code.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migra...
Python best practices, FastAPI, Pandas ve veri bilimi kütüphaneleri kullanımı.
Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。