benchmark

benchmark is a skill for Claude Code from soniqo/speech-swift. It costs 0 tokens per session (1,254 once invoked), scanned A, original, Apache-2.0.

A benchmarking tool for measuring speech-processing systems. It reports measures such as word error rate, processing speed, memory use, throughput, and diarization error rate.

In plain words
What is it for?
Use it to benchmark automatic speech recognition, text-to-speech, voice activity detection, and speaker diarization, either fully or with quick smoke tests.
Why use it?
It lets you compare engines or variants with recorded test data instead of judging performance by guesswork.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/benchmark_vad.py --compare --num-files 5 2>&1.

Good fit Use it to benchmark automatic speech recognition, text-to-speech, voice activity detection, and speaker diarization, either fully or with quick smoke tests.

Compare 6 skills from other repositories ↓
About the project

Speech Swift is a collection of Apple Silicon speech tools for recognizing, generating, transforming, and analyzing audio locally with MLX Swift and CoreML. It is for Mac and iOS applications that need on-device speech features such as transcription, voice agents, synthesis, and speaker identification; the catalogue entries provide instructions and skills for using it.

soniqo/speech-swift · 1,244 stars · on GitHub · soniqo.audio

Install

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.

Clone the repo
git clone --depth 1 https://github.com/soniqo/speech-swift
agentmods
npx agentmods add skills/soniqo/speech-swift/benchmark

Made for: Claude Code.

Wrote 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.

agentmods badge for benchmark

README.md
[![agentmods](https://agentmods.dev/badge/skills/soniqo/speech-swift/benchmark/github.svg)](https://agentmods.dev/skills/soniqo/speech-swift/benchmark)
Your own site
<a href="https://agentmods.dev/skills/soniqo/speech-swift/benchmark"><img src="https://agentmods.dev/badge/skills/soniqo/speech-swift/benchmark/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.

agentmods 80×15 button for benchmark

Your own site · 80×15
<a href="https://agentmods.dev/skills/soniqo/speech-swift/benchmark"><img src="https://agentmods.dev/badge/skills/soniqo/speech-swift/benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,254 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium analysis-evasion · line 1
    Suspicious Unicode normalization or mixed-script content
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
How audits are shown
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 5.1 $0.00000 $0.01254
Opus 5.5 $0.00000 $0.00502
Sonnet 5.5 $0.00000 $0.00251
Haiku 4.5 $0.00000 $0.00125

Measured 5d ago against content hash cbbf8090a253, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

benchmark 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 5d 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.

.claude/skills/benchmark/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Benchmark

Run benchmarks using the release build. Build first with /build.

Usage

  • /benchmark asr — full WER + RTF + peakRSS + throughput on a labeled dataset (LibriSpeech-style dir or .tsv manifest). Extra args pass through to asr-bench. Requires BENCH_DATASET env var or --dataset <path> in the trailing args.
  • /benchmark asr-quick — single-file RTF smoke test (no WER, no dataset required). Equivalent to the old asr behavior.
  • /benchmark tts — synthesize test text, report RTF
  • /benchmark vad — VAD on VoxConverse (all engines)
  • /benchmark diarize — DER on VoxConverse (requires downloaded test set)

Examples

Compare our MLX quantizations on LibriSpeech test-clean (WER + RTF + peakRSS, each engine isolated in its own process so RSS reflects per-engine cost):

BENCH_DATASET=$HOME/datasets/LibriSpeech/test-clean /benchmark asr \
  --engines qwen3-mlx-0.6b-4bit qwen3-mlx-0.6b-8bit \
  --isolated --limit 50

Default engine set (qwen3-coreml + parakeet + whisperkit) on a TSV manifest:

/benchmark asr --dataset bench.tsv --limit 100 --output /tmp/run.json
module="$1"
shift || true
cli=".build/release/speech"
bench=".build/release/asr-bench"

case "$module" in
  asr)
    if [ ! -x "$bench" ]; then
      echo "asr-bench binary missing — run /build first (release)." >&2
      exit 1
    fi
    # Honor BENCH_DATASET if --dataset isn't already in the trailing args.
    has_dataset=0
    for a in "$@"; do
      if [ "$a" = "--dataset" ]; then has_dataset=1; break; fi
    done
    if [ "$has_dataset" = "0" ] && [ -n "$BENCH_DATASET" ]; then
      set -- --dataset "$BENCH_DATASET" "$@"
    fi
    "$bench" "$@" 2>&1
    ;;
  asr-quick)
    $cli transcribe Tests/Qwen3ASRTests/Resources/test_audio.wav 2>&1
    ;;
  tts)
    $cli speak "The quick brown fox jumps over the lazy dog." --output /tmp/bench_tts.wav 2>&1
    ;;
  vad)
    python3 scripts/benchmark_vad.py --compare --num-files 5 2>&1
    ;;
  diarize)
    python3 scripts/benchmark_diarization.py --num-files 5 2>&1
    ;;
  *)
    echo "Usage: /benchmark [asr|asr-quick|tts|vad|diarize] [args...]"
    echo "  asr       — full WER + RTF + peakRSS via asr-bench (needs dataset)"
    echo "  asr-quick — single-file RTF smoke test (no dataset)"
    ;;
esac

Read the full file on GitHub · 120 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. 5d ago Changed · +1 lines cbbf8090a253
  2. 1mo ago First seen · 119 lines · 0 tokens per session scan A ea26a24f6d40

Subscribe to this mod's changes

benchmark is a skill published in the GitHub repository soniqo/speech-swift (1,244 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,254 tokens. 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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