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Found 21 Skills
This skill handles file format conversions across documents (PDF, DOCX, Markdown, HTML, TXT), data files (JSON, CSV, YAML, XML, TOML), and images (PNG, JPG, WebP, SVG, GIF). Use when the user requests converting, transforming, or exporting files between formats. Generates conversion code dynamically based on the specific request.
Validates code changes against DeepRead's mandatory patterns and standards defined in AGENTS.md. Use this after writing or modifying code to catch violations before committing.
Migrates Honcho Python SDK code from v1.6.0 to v2.0.0. Use when upgrading honcho package, fixing breaking changes after upgrade, or when errors mention AsyncHoncho, observations, Representation class, .core property, or get_config methods.
Brief description of what this skill does and when to use it. Be specific about capabilities and use cases to help agents decide when to load this skill.
Guide for using ty, the extremely fast Python type checker and language server. Use this when type checking Python code or setting up type checking in Python projects.
Apply production-ready Databricks SDK patterns for Python and REST API. Use when implementing Databricks integrations, refactoring SDK usage, or establishing team coding standards for Databricks. Trigger with phrases like "databricks SDK patterns", "databricks best practices", "databricks code patterns", "idiomatic databricks".
Discovers and indexes Python code in skills, enabling cross-skill imports. Use when importing functions from other skills or analyzing skill codebases.
Galaxy code linting, formatting, and type checking. Run checks, auto-fix formatting, Python lint, client lint, mypy type checks. Use for: ruff, flake8, black, isort, darker, autoflake, pyupgrade, eslint, prettier, mypy, tox, make format, make diff-format, code style, lint failures, CI lint checks, formatting errors, type errors, codespell, redocly, api schema, xsd, config lint.
Comprehensive code reviewer for Java and Python implementations focusing on correctness, efficiency, code quality, and algorithmic optimization. Reviews LeetCode solutions, data structures, and algorithm implementations. Use when reviewing code, checking solutions, or providing feedback on implementations.