Software Development Skills

Expert-level guidance for creating high-quality Claude Code skills. Use alongside Anthropic's skill-creator when creating new skills, improving existing skills, or needing guidance on skill content quality. Complements basic skill mechanics with research-driven content development, XML tag structuring, decision frameworks over mechanics, cross-references between skills, and systematic validation.

Fish shell scripting judgment frameworks and critical idioms. Use when writing Fish scripts or shell automation. Focuses on when to use Fish vs bash, macOS/Fedora compatibility requirements, and Fish-specific patterns that prevent bugs (universal variable anti-patterns, wrapper functions, interactive guards).

Functional programming principles, patterns, and practices. Use when working with functional languages (Racket, Clojure, Erlang, Haskell, Idris, Scheme, OCaml, F, Elixir, etc.) without language-specific skills available, or when applying functional paradigms in multi-paradigm languages.

Git commit standards, branch strategy, and LLM-assisted development workflows. Use when making commits, managing branches, or working in high-velocity LLM-assisted development contexts. Covers atomic commits, conventional commits, branching strategies (trunk-based, GitHub flow), merge vs rebase decisions, and recovery patterns.

Multi-source research orchestrated across a persistent agent team. Use for queries asking for research-style investigation of a topic — comparing, contrasting, surveying, investigating, evaluating, deeply researching, doing a literature review, or any similar research intent — or that ask what people are saying publicly about a topic (discourse, expert opinion, industry consensus, and related framings). Example phrasings (illustrative, not exhaustive): "compare X and Y", "survey the state of X", "deep dive on X", "what's been said about X", "research the trade-offs of X vs Y". Match the underlying research intent, not the exact wording. Decomposes the topic into subtopics, spawns specialist researchers, sample-verifies primary sources, and produces a unified report with ACM citations and iterative refinement. Prefer over single-agent search when the topic spans multiple facets or source diversity matters. Skip when answerable by a single search or a single doc lookup.

Java-specific tooling, documentation standards, testing practices, and modern idioms. Use when working with Java code or Java-based projects on the JVM.

Logic programming thinking patterns and relational design principles. Use when working with logic languages (Prolog, miniKanren, Datalog, OWL2, Answer Set Programming) or applying declarative, constraint-based approaches in multi-paradigm systems.

macOS-specific development patterns, platform APIs, and decision frameworks. Use when developing Mac apps, macOS applications, Cocoa/AppKit code, or making SwiftUI vs AppKit decisions. Covers NSWindow management, NSDocument architecture, sandboxing, code signing, notarization, and macOS UI patterns. Applies to Mac Catalyst considerations.

Object-oriented design principles, patterns, and practices. Use when working with object-oriented languages (Java, C, C++, Python, Ruby, Swift, etc.) without language-specific skills available, or when applying OOP in multi-paradigm codebases.

Python-specific idioms, philosophy, and expert-level patterns. Use when working with Python code, including Jupyter notebooks (.ipynb). Covers Pythonic thinking, common pitfalls from other language backgrounds, testing ecosystem navigation, type hints trade-offs, and when to use modern Python features.

SWI-Prolog-specific tooling, standards, and idioms. Use when working with SWI-Prolog code. Emphasizes relational thinking, steadfastness, DCGs, constraints, and mandatory testing with PlUnit.

Swift-specific idioms, tooling, and philosophy. Use when working with Swift code. Emphasizes protocol-oriented programming, value semantics, strict concurrency (Swift 6+), and compile-time safety guarantees.