Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/gertsylvest/meta-teamnpx agentmods add skills/gertsylvest/meta-team/cargo-bench-rtWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gertsylvest/meta-team/cargo-bench-rt)<a href="https://agentmods.dev/skills/gertsylvest/meta-team/cargo-bench-rt"><img src="https://agentmods.dev/badge/skills/gertsylvest/meta-team/cargo-bench-rt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gertsylvest/meta-team/cargo-bench-rt"><img src="https://agentmods.dev/badge/skills/gertsylvest/meta-team/cargo-bench-rt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00909 |
| Opus 5 | $0.00026 | $0.00454 |
| Sonnet 5 | $0.00011 | $0.00182 |
| Haiku 4.5 | $0.00005 | $0.00091 |
Grade A, and why
cargo-bench-rt 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cargo Bench RT
Audio DSP correctness is not enough — the implementation must also fit within the real-time buffer budget. At 48 kHz with a 128-sample block (the AudioWorklet quantum), a process() call has roughly 2.67 ms to complete; on a typical native build with 256-sample blocks at 48 kHz the budget is ~5.33 ms.
This skill wraps Criterion in two modes:
- First run / baseline mode — establishes a baseline measurement of a named bench and commits it.
- Regression mode — compares the current measurement against the committed baseline and fails if the regression exceeds a configurable percentage.
The intent mirrors the c-audio-engineer's "profile the callback against the real-time budget" rule, applied to Rust DSP crates.
Requirements
- A
[[bench]]entry in the crate'sCargo.tomlfor the named benchmark. - The
criterioncrate as adev-dependency. - A bench source file at
benches/<bench-name>.rsusing the Criterion harness.
Typical Criterion bench skeleton:
use criterion::{black_box, criterion_group, criterion_main, Criterion};
fn bench_process(c: &mut Criterion) {
let mut state = my_dsp::Processor::new(48_000.0);
let mut buf = [0.0_f32; 128];
c.bench_function("process_128", |b| {
b.iter(|| state.process(black_box(&mut buf)));
});
}
criterion_group!(benches, bench_process);
criterion_main!(benches);
Instructions
The arguments are in $ARGUMENTS. Pass them directly to the bench script:
bash "$(dirname "$0")/bench.sh" $ARGUMENTS
- Argument 1: crate directory.
- Argument 2: bench name (matches the
[[bench]] name = "..."in Cargo.toml). - Optional
--save-baseline: overwrite the baseline with the current measurement. Use after a deliberate performance change. - Optional
--budget-pct N(default5): regression budget in percent. The bench fails if the new measurement is more than N% slower than the baseline.
Output sections
| Section | What it reports |
|---|---|
BENCH |
Criterion run summary (mean, std dev, throughput) |
BUDGET |
Pass/fail vs the baseline, with the actual delta |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 83 lines · 53 tokens per session scan A 58ff49381aa4
cargo-bench-rt is a skill published in the GitHub repository gertsylvest/meta-team (5 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 909 once invoked, about $0.0003 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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