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/stefanthecode/dotnet-ai-toolkit/benchmarkdotnet-setupnpx skills add StefanTheCode/dotnet-ai-toolkit --skill benchmarkdotnet-setupgit clone --depth 1 https://github.com/StefanTheCode/dotnet-ai-toolkitWhat 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 | $0.00100 | $0.00693 |
| Opus 5 | $0.00050 | $0.00347 |
| Sonnet 5 | $0.00020 | $0.00139 |
| Haiku 4.5 | $0.00010 | $0.00069 |
Grade A, and why
benchmarkdotnet-setup 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BenchmarkDotNet Setup
Write correct BenchmarkDotNet benchmarks (no common pitfalls) and read the results properly — so "which is faster" is answered with data, not vibes.
Input — point it at your code
Works on a target: a file, folder, project, or GitHub URL. Identify the methods/implementations to compare; if the user pasted results, go straight to interpretation.
Project + benchmark class
dotnet add package BenchmarkDotNet
[MemoryDiagnoser] // allocations matter as much as time
[Orderer(SummaryOrderPolicy.FastestToSlowest)]
public class StringJoinBenchmarks
{
private readonly string[] _items = Enumerable.Range(0, 1000).Select(i => i.ToString()).ToArray();
[Benchmark(Baseline = true)]
public string StringConcat() { var s = ""; foreach (var i in _items) s += i; return s; }
[Benchmark]
public string StringBuilder_() { var sb = new StringBuilder(); foreach (var i in _items) sb.Append(i); return sb.ToString(); }
[Benchmark]
public string StringJoin() => string.Join("", _items);
}
// Program.cs: BenchmarkRunner.Run<StringJoinBenchmarks>();
Run in Release: dotnet run -c Release.
Pitfalls the skill prevents
- Benchmarking in Debug, or without
BenchmarkRunner(JIT/optimizations differ). - Dead-code elimination — return the result so the work isn't optimized away.
- Setup work inside the
[Benchmark]method — move it to[GlobalSetup]. - Comparing without a
[Baseline]— you need a reference point. - Tiny inputs that measure noise, not the algorithm.
Reading the summary
- Mean (ns/us/ms) — central tendency; check StdDev/Error for noise.
- Ratio — vs baseline (the headline comparison).
- Gen0/1/2 + Allocated — allocations and GC pressure; often the real story, not raw time.
- A faster method that allocates 10× more may lose under real load — weigh both.
Principles
- Measure the realistic input size and shape, not a toy.
- Allocations are a first-class result — keep
[MemoryDiagnoser]on. - One variable at a time; keep benchmarks isolated and deterministic.
- Don't micro-optimize a path that isn't hot — confirm it matters first (
hotpath-profiler-assistant).
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.
- 2d ago First seen · 60 lines · 100 tokens per session scan A e4b255f2e07b
benchmarkdotnet-setup is a skill published in the GitHub repository StefanTheCode/dotnet-ai-toolkit (19 stars, last pushed 23d ago), licensed MIT. It adds 100 tokens to every session and 693 once invoked, about $0.0005 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 2026-08-30.
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