AI Coding Skills for Rust

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.

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.

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.

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.

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.

Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.

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.

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

Tauri development guidelines for building cross-platform desktop applications with TypeScript, Rust, and modern web technologies

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

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.

Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.

Comprehensive Rust coding guidelines with 179 rules across 14 categories. Use when writing, reviewing, or refactoring Rust code. Covers ownership, error handling, async patterns, API design, memory optimization, performance, testing, and common anti-patterns. Invoke with /rust-skills.

Guide for writing Apollo Router native Rust plugins. Use this skill when: (1) users want to create a new router plugin, (2) users want to add service hooks (router_service, supergraph_service, execution_service, subgraph_service), (3) users want to modify an existing router plugin, (4) users need to understand router plugin patterns or the request lifecycle. (5) triggers on requests like "create a new plugin", "add a router plugin", "modify the X plugin", or "add subgraph_service hook".

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.