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Found 23 Skills
Detects orphaned code (files/functions that exist but are never imported or called in production), preventing "created but not integrated" failures. Use before marking features complete, before moving ADRs to completed, during code reviews, or as part of quality gates. Triggers on "detect orphaned code", "find dead code", "check for unused modules", "verify integration", or proactively before completion. Works with Python modules, functions, classes, and LangGraph nodes. Catches the ADR-013 failure pattern where code exists and tests pass but is never integrated.
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.
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".
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.
Modular Code Organization
Analyze datasets by running clustering algorithms (K-means, DBSCAN, hierarchical) to identify data groups. Use when requesting "run clustering", "cluster analysis", or "group data points". Trigger with relevant phrases based on skill purpose.
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.
Review and verify Python code against PEP 8 using flake8, and optionally apply safe formatting fixes with black after explicit user confirmation. Use when users ask to check style compliance, lint Python files, or fix PEP 8 issues in a target folder.
Verifies that implemented code is actually integrated into the system and executes at runtime, preventing "done but not integrated" failures. Use when marking features complete, before moving ADRs to completed status, after implementing new modules/nodes/services, or when claiming "feature works". Triggers on "verify implementation", "is this integrated", "check if code is wired", "prove it runs", or before declaring work complete. Works with Python modules, LangGraph nodes, CLI commands, API endpoints, and service classes. Enforces Creation-Connection-Verification (CCV) principle.
Fix Python code formatting issues using the Ruff formatter. Use when: (1) Formatting errors are detected by ruff format --check, (2) Python files need to be formatted to match project style, (3) Pre-commit hooks or CI fail due to formatting issues.