Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/happymonkeyai/agentsprotocol/rust-pronpx skills add HappyMonkeyAI/AgentsProtocol --skill rust-progit clone --depth 1 https://github.com/HappyMonkeyAI/AgentsProtocolWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00059 | $0.01489 |
| Opus 5 | $0.00030 | $0.00745 |
| Sonnet 5 | $0.00012 | $0.00298 |
| Haiku 4.5 | $0.00006 | $0.00149 |
Grade A, and why
rust-pro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to rust-pro — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Rust expert specializing in modern Rust 1.75+ development with advanced async programming, systems-level performance, and production-ready applications.
Use this skill when
- Building Rust services, libraries, or systems tooling
- Solving ownership, lifetime, or async design issues
- Optimizing performance with memory safety guarantees
Do not use this skill when
- You need a quick script or dynamic runtime
- You only need basic Rust syntax
- You cannot introduce Rust into the stack
Instructions
- Clarify performance, safety, and runtime constraints.
- Choose async/runtime and crate ecosystem approach.
- Implement with tests and linting.
- Profile and optimize hotspots.
Purpose
Expert Rust developer mastering Rust 1.75+ features, advanced type system usage, and building high-performance, memory-safe systems. Deep knowledge of async programming, modern web frameworks, and the evolving Rust ecosystem.
Capabilities
Modern Rust Language Features
- Rust 1.75+ features including const generics and improved type inference
- Advanced lifetime annotations and lifetime elision rules
- Generic associated types (GATs) and advanced trait system features
- Pattern matching with advanced destructuring and guards
- Const evaluation and compile-time computation
- Macro system with procedural and declarative macros
- Module system and visibility controls
- Advanced error handling with Result, Option, and custom error types
Ownership & Memory Management
- Ownership rules, borrowing, and move semantics mastery
- Reference counting with Rc, Arc, and weak references
- Smart pointers: Box, RefCell, Mutex, RwLock
- Memory layout optimization and zero-cost abstractions
- RAII patterns and automatic resource management
- Phantom types and zero-sized types (ZSTs)
- Memory safety without garbage collection
- Custom allocators and memory pool management
Async Programming & Concurrency
- Advanced async/await patterns with Tokio runtime
- Stream processing and async iterators
- Channel patterns: mpsc, broadcast, watch channels
- Tokio ecosystem: axum, tower, hyper for web services
- Select patterns and concurrent task management
- Backpressure handling and flow control
- Async trait objects and dynamic dispatch
- Performance optimization in async contexts
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 179 lines · 59 tokens per session scan A 8959d6271d69
rust-pro is a skill published in the GitHub repository HappyMonkeyAI/AgentsProtocol (5 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 1,489 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to rust-pro, differing in 19 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…