Scripting

This skill analyzes code for design quality improvements across 8 dimensions: Naming, Object Calisthenics, Coupling & Cohesion, Immutability, Domain Integrity, Type System, Simplicity, and Performance. Ensures rigorous, evidence-based analysis by: (1) Understanding code flow first via implementation-analysis protocol, (2) Systematically evaluating each dimension with specific criteria, (3) Providing actionable findings with file:line references. Triggers when users request: code analysis, design review, refactoring opportunities, code quality assessment, architecture evaluation.

This skill should be used when fixing bugs, implementing features, debugging issues, or making code changes. Ensures understanding of code flow before implementation by: (1) Tracing execution path with specific file:line references, (2) Creating lightweight text diagrams showing class.method() flows, (3) Verifying understanding with user. Prevents wasted effort from assumptions or guessing. Triggers when users request: bug fixes, feature implementations, refactoring, TDD cycles, debugging, code analysis.

Intensive mathematical analysis for numerical stability, algorithm correctness, and alignment with authoritative standards. Triggers: math review, numerical stability, algorithm correctness, mathematical verification, scientific computing, numerical analysis, derivation check Use when: reviewing math-heavy code, verifying algorithm correctness, checking numerical stability, aligning with mathematical standards DO NOT use when: general algorithm review - use architecture-review. DO NOT use when: performance optimization - use parseltongue:python-performance. Use this skill for mathematical code verification.

Shared testing quality metrics and standards for cross-plugin use. Referenced by pensive:test-review and parseltongue:python-testing. Triggers: testing standards, quality metrics, coverage thresholds, test quality, anti-patterns, testing best practices, quality gates Use when: evaluating test quality, setting coverage thresholds, identifying testing anti-patterns, establishing quality standards DO NOT use when: simple scripts without quality requirements. Consult this skill when establishing testing quality standards.

Systematic methodology to reduce skill file size through externalization, consolidation, and progressive loading patterns. Triggers: large skill, skill optimization, skill size, 300 lines, inline code, skill refactoring, skill context reduction, skill modularization Use when: skills exceed 300 lines, multiple code blocks (10+) with similar functionality, heavy Python inline with markdown, functions >20 lines embedded DO NOT use when: skill is under 300 lines and well-organized. DO NOT use when: creating new skills - use modular-skills instead. Consult this skill when skills-eval shows "Large skill file" warnings.

Foundational infrastructure patterns shared across all leyline skills. Triggers: leyline patterns, shared infrastructure, python imports, config patterns, leyline foundation, cross-skill patterns Use when: other leyline skills need common patterns, creating new infrastructure skills, ensuring consistency across leyline plugin DO NOT use directly: this skill is infrastructure for other leyline skills. This skill provides shared patterns consumed by other leyline skills.

Create distributable Python packages with proper structure and publishing. Triggers: Python packaging, pyproject.toml, uv, pip, PyPI, distribution, CLI tools, entry points, package structure, publishing Use when: creating Python packages, configuring pyproject.toml, setting up entry points, publishing to PyPI, CI/CD for packages DO NOT use when: testing packages - use python-testing instead. DO NOT use when: optimizing package performance - use python-performance. Consult this skill for Python package creation and distribution.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Triggers: profiling, optimization, cProfile, memory profiler, bottleneck, slow code, performance, benchmarking, py-spy, tracemalloc Use when: debugging slow code, identifying bottlenecks, optimizing memory, benchmarking performance, production profiling DO NOT use when: async concurrency - use python-async instead. DO NOT use when: CPU/GPU system monitoring - use conservation:cpu-gpu-performance. Consult this skill for Python performance profiling and optimization.

Expert-level Rust audits covering ownership, concurrency, unsafe blocks, traits, and Cargo dependencies. Triggers: Rust review, ownership analysis, borrowing, unsafe audit, concurrency, Cargo dependencies, lifetime annotations, trait bounds Use when: reviewing Rust code, auditing unsafe blocks, analyzing ownership patterns, scanning Cargo dependencies for security DO NOT use when: general code review without Rust - use unified-review. DO NOT use when: performance profiling - use parseltongue:python-performance pattern. Use this skill for Rust-specific code audits.

JS/TS conventions for syntax, modules, and types. Use when writing or reviewing JavaScript/TypeScript code.

Sets up a Mac for ButterCut. Installs all required dependencies (Homebrew, Ruby, Python, FFmpeg, WhisperX). Use when user says "install buttercut", "set up my mac", "get started", "first time setup", "install dependencies" or "check my installation".

Use bdg CLI for browser automation via Chrome DevTools Protocol. Provides direct CDP access (60+ domains, 300+ methods) for DOM queries, navigation, screenshots, network control, and JavaScript execution. Use this skill when you need to automate browsers, scrape dynamic content, or interact with web pages programmatically.

Use when implementing Stripe webhook endpoints and getting 'Raw body not available' or signature verification errors - provides raw body parsing solutions and subscription period field fixes across frameworks

Write focused tests for core user flows and critical paths with clear test names, behavior-focused assertions, mocked external dependencies, and fast execution, deferring edge case testing until explicitly required. Use this skill when creating or modifying test files, writing unit tests, integration tests, or test cases for any feature. Apply when writing test files (test/, __tests__/, spec/, .test.js, .spec.ts, test_*.py), implementing tests for core user workflows, testing critical business logic, mocking external dependencies (databases, APIs, file systems), writing descriptive test names, creating fast-running unit tests, or adding tests at logical completion points of feature development. Use for any task involving test creation, test coverage, test strategy, or test-driven development.

Expert assistant for using litdb - a literature and document database for scientific research

Write clean, consistent code following naming conventions, automated formatting, DRY principles, small focused functions, and meaningful variable names across all languages and files. Use this skill when writing or modifying any code file in any language or framework. Apply when naming variables, functions, classes, or files, when refactoring code to remove duplication, when breaking down large functions into smaller focused ones, when cleaning up dead code or unused imports, when ensuring consistent indentation and formatting, when choosing descriptive names over abbreviations, or when following the project's linting and formatting rules (ESLint, Prettier, RuboCop, Black, etc.). Use for any task involving code organization, readability, maintainability, or style consistency across the codebase.

Use when encountering TypeScript any types, type errors, or lax type checking - eliminates type holes and enforces strict type safety through proper interfaces, type guards, and module augmentation

Port Ruby gems with native C extensions to Fil-C. Use when fixing gem compilation errors, VALUE/int type mismatches, rb_attr/rb_protect issues, or using ast-grep for Ruby C extensions.

Use this when you have finished making code changes and you are ready to update the documentation based on those changes.

Use when discussing or working with DeepEval (the python AI evaluation framework)