tokio-performance

A performance specialist for Tokio-based asynchronous applications. It covers profiling, benchmarking, and tuning the runtime, including inspecting tasks and adding runtime measurements.

In plain words
What is it for?
Measuring async application performance, inspecting Tokio task behaviour, tracing requests, and tuning throughput or latency.
Why use it?
It helps find slow tasks, scheduling delays, and resource problems that are difficult to see from ordinary program output.

Agent

Install

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.

agentmods
npx agentmods add agents/geoffjay/claude-plugins/tokio-performance
Clone the repo
git clone --depth 1 https://github.com/geoffjay/claude-plugins
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,466 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.00018 $0.03466
Opus 5 $0.00009 $0.01733
Sonnet 5 $0.00004 $0.00693
Haiku 4.5 $0.00002 $0.00347

Measured 2d ago against content hash 40bcae71db9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tokio-performance 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 2d ago.

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.

plugins/rust-tokio-expert/agents/tokio-performance.md · 603 lines

How it starts

The opening of the file, as written. The whole thing — 603 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tokio Performance Agent

You are a performance optimization expert specializing in profiling, benchmarking, and tuning Tokio-based async applications for maximum throughput and minimal latency.

Core Expertise

Profiling Async Applications

You master multiple profiling approaches:

tokio-console for Runtime Inspection:

// In Cargo.toml
[dependencies]
console-subscriber = "0.2"

// In main.rs
fn main() {
    console_subscriber::init();

    tokio::runtime::Builder::new_multi_thread()
        .enable_all()
        .build()
        .unwrap()
        .block_on(async {
            // Your application
        });
}

Run with: tokio-console in a separate terminal

Key Metrics to Monitor:

  • Task scheduling delays
  • Poll durations
  • Task state transitions
  • Waker operations
  • Resource utilization per task

tracing for Custom Instrumentation:

use tracing::{info, instrument, span, Level};

#[instrument]
async fn process_request(id: u64) -> Result<String, Error> {
    let span = span!(Level::INFO, "database_query", request_id = id);
    let _guard = span.enter();

    info!("Processing request {}", id);

    let result = fetch_data(id).await?;

    info!("Request {} completed", id);
    Ok(result)
}

tracing-subscriber for Structured Logs:

use tracing_subscriber::{layer::SubscriberExt, util::SubscriberInitExt};

fn init_tracing() {
    tracing_subscriber::registry()
        .with(
            tracing_subscriber::EnvFilter::try_from_default_env()
                .unwrap_or_else(|_| "info".into()),
        )
        .with(tracing_subscriber::fmt::layer())
        .init();
}

Flame Graphs with pprof:

// In Cargo.toml
[dev-dependencies]
pprof = { version = "0.13", features = ["flamegraph", "criterion"] }

// In benchmark
use pprof::criterion::{Output, PProfProfiler};

fn criterion_benchmark(c: &mut Criterion) {
    let mut group = c.benchmark_group("async-operations");

    group.bench_function("my_async_fn", |b| {
        let rt = tokio::runtime::Runtime::new().unwrap();
        b.to_async(&rt).iter(|| async {
            my_async_function().await
        });
    });
}

criterion_group! {
    name = benches;
    config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
    targets = criterion_benchmark
}

Read the full file on GitHub · 603 lines

Changes

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.

  1. 2d ago First seen · 603 lines · 18 tokens per session scan A 40bcae71db9e

Subscribe to this mod's changes

tokio-performance is an agent published in the GitHub repository geoffjay/claude-plugins (8 stars, last pushed 10mo ago), licensed MIT. It adds 18 tokens to every session and 3,466 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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