AI Coding Skills for Rust

Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.

Generate a production-ready command-line tool -- scaffold a complete CLI application with subcommand parsing, interactive prompts with validation, colored and structured output (tables, spinners, progress bars), JSON output mode for scripting, XDG-compliant config management, custom error types with exit codes, and distribution setup for publishing. Supports Node.js (Commander.js, Inquirer, chalk, ora), Python (Typer, Rich, httpx, Pydantic), Go (Cobra, Bubble Tea, Lip Gloss, Viper, goreleaser), and Rust (clap derive, dialoguer, console, comfy-table). Build a CLI, create command-line app, generate terminal tool, scaffold CLI utility, new CLI project.

Guide for writing idiomatic Rust code based on Apollo GraphQL's best practices handbook. Use this skill when: (1) writing new Rust code or functions, (2) reviewing or refactoring existing Rust code, (3) deciding between borrowing vs cloning or ownership patterns, (4) implementing error handling with Result types, (5) optimizing Rust code for performance, (6) writing tests or documentation for Rust projects.

Probe for hardcoded secrets, injection surfaces, unguarded routes, business logic flaws, and platform-specific weaknesses across backend (Node, Go, Java, Python, Rust), frontend (React, Angular, Vue), and mobile (iOS, Android, Flutter) codebases. Use when performing security audits, vulnerability scans, secrets detection, or penetration testing.

Configure linting, formatting, and editor integration for any stack. Sets up ESLint 9 or Biome for JS/TS, Ruff for Python, golangci-lint for Go, Clippy for Rust, RuboCop for Ruby, or dart analyze for Flutter. Adds Prettier or equivalent formatter, .editorconfig, and VS Code format-on-save. Use when you need to add a linter, fix formatting inconsistencies, migrate from legacy lint tools, or set up code style enforcement.

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

Auto-detects the current project's technology stack and hot-loads context-appropriate skills at session start using Claude Code's SessionStart hook with reloadSkills: true. Detects Node.js/TypeScript, Next.js, Python, Rust, Go, Ruby, and monorepo layouts. Emits a .claude/dynamic-context.md with the detected stack and recommended skill list, then signals Claude Code to reload skills before the first agent turn.

Grades a specified set of test methods individually and produces a concise table mapping each test (fully-qualified name) to a letter grade (A–F), a score band, and a one-line note — designed to be posted as a PR comment. Use when the caller wants per-test feedback on a curated list of methods (for example, the new or modified tests in a pull request), not a suite-wide audit. Polyglot: .NET, Python, TS/JS, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, C++. Input is a list of test methods (or method bodies / file+line spans); output is a compact markdown table plus a short summary. DO NOT USE FOR: full suite audits (use test-quality-auditor agent or test-anti-patterns), writing new tests (use code-testing-generator agent or writing-mstest-tests), fixing failures, or measuring code coverage.

Performs pseudo-mutation analysis on production code in any language to find gaps in existing tests. Use when the user asks to find weak or shallow tests, discover untested edge cases, or check whether tests would catch a bug — e.g. "would my tests catch it if someone changed the code", "would a subtle logic or boundary change slip past the current tests", "are my tests strong enough to catch a subtle bug". Evaluates test effectiveness through mutation-style reasoning: analyzes mutation points (boundaries, boolean flips, null returns, exception removal, arithmetic changes) and checks whether tests would detect each. Polyglot: .NET, Python, TS/JS, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, C++. DO NOT USE FOR: writing new tests (use code-testing-agent, or writing-mstest-tests for MSTest), detecting anti-patterns (use test-anti-patterns), measuring assertion diversity (use assertion-quality), or running actual mutation testing tools (Stryker, mutmut, PIT, cargo-mutants).

Parse-only static analysis that pairs source files with the tests referencing them and emits JSON listing untested files ordered by API surface, each with a suggested_test_path. Roslyn engine for C#/.NET (namespace-aware), tree-sitter engine for polyglot repos (Python, TS/JS, Go, Java, Rust, Ruby). USE FOR: where to write tests next, which files have no tests, find untested code, build a source-to-test pairing map, prioritized test-gap worklist. DO NOT USE FOR: line/branch coverage or CRAP risk (use coverage-analysis); whether existing tests are strong (use test-gap-analysis or assertion-quality).

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Expert in Rust development with focus on safety, performance, and async programming

Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more.

Best practices and guidelines for Turbopack, the Rust-powered incremental bundler for Next.js and modern web development

Expert guidelines for Solana program development with Rust, Anchor framework, and Web3.js integration

Performs comprehensive Rust security review for safe/unsafe boundary issues, memory safety in unsafe blocks, concurrency hazards, panic-induced DoS, FFI safety, and async runtime mistakes. Use when auditing Rust crates, services, or libraries — particularly those with `unsafe`, FFI, or concurrent code.