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AI resources

  • An experimental tool-invocation companion for 'just-bash' that allows JavaScript code in the 'js-exec' environment to call various automated tools as bash commands.
  • Provides comprehensive guidelines for writing effective code documentation, covering docstrings, JSDoc, dartdoc, and implementation comments across Dart, Python, and TypeScript.
  • Provides guidance on language and framework specific security best practices, including reviews and suggestions for improvements in secure coding.
  • Enhances Python LLM applications by setting up an automated evaluation pipeline to define criteria, instrument applications, build datasets, and analyze results for quality assurance.
  • Provides tools and guidelines for authoring and editing MPS baseLanguage (Java) nodes, including various paths for syntax parsing and persistent reference management.
  • The Brave Search CLI (`bx`) allows users to perform comprehensive web searches using the Brave Search API, optimized for AI agents and LLMs. It enables efficient search queries with pre-extracted, relevance-scored content and supports various commands for documentation lookup, AI-generated answers, and more.
  • Connect and interact with Spanner data using natural language queries.
  • Generates Python code using BigQuery DataFrames for data processing, analysis, and machine learning tasks.
  • Use the DuckDB Python client (duckdb 2.0) for querying DataFrames, Parquet, or CSV with SQL. Learn to handle connections, execute SQL commands, manage results, and work with parameters effectively.
  • Ban code patterns using Tree Sitter AST queries. This tool rejects edits that introduce banned patterns unless justified with a comment.