A speech-recognition model that turns spoken audio into text, identifies the spoken language, and can translate speech into English. It supports 99 languages and several model sizes.

Use it for podcast, video, and meeting transcription, speech-to-text applications, language identification, English translation, and other audio-processing tasks.

It removes the need to transcribe recordings by hand and can handle multilingual or noisy audio.

whisper — Skill for Claude Code and Codex by Tommy-yw/RunbookHermes

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.

Any agent

npx skills add Tommy-yw/RunbookHermes --skill whisper

Clone the repo

git clone --depth 1 https://github.com/Tommy-yw/RunbookHermes

Made for: Claude Code, Codex.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tommy-yw/runbookhermes/whisper/github.svg)](https://agentmods.dev/skills/tommy-yw/runbookhermes/whisper)

Your own site

<a href="https://agentmods.dev/skills/tommy-yw/runbookhermes/whisper"><img src="https://agentmods.dev/badge/skills/tommy-yw/runbookhermes/whisper/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tommy-yw/runbookhermes/whisper"><img src="https://agentmods.dev/badge/skills/tommy-yw/runbookhermes/whisper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,035 The whole file, excluding the scripts and references it only reads on demand.

Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin 97% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5.1	$0.00067	$0.02035
Opus 5.5	$0.00027	$0.00814
Sonnet 5.5	$0.00013	$0.00407
Haiku 4.5	$0.00007	$0.00203

Measured 2mo ago against content hash 060e2cc18ff6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

whisper scanned grade B with 1 finding 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 2mo 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

# Ubuntu: sudo apt install ffmpeg

Origin

This is a copy

97% identical to multimodal-whisper — 12 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.

optional-skills/mlops/whisper/SKILL.md · 321 lines

How it starts

The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Whisper - Robust Speech Recognition

OpenAI's multilingual speech recognition model.

When to use Whisper

Use when:

Speech-to-text transcription (99 languages)
Podcast/video transcription
Meeting notes automation
Translation to English
Noisy audio transcription
Multilingual audio processing

Metrics:

72,900+ GitHub stars
99 languages supported
Trained on 680,000 hours of audio
MIT License

Use alternatives instead:

AssemblyAI: Managed API, speaker diarization
Deepgram: Real-time streaming ASR
Google Speech-to-Text: Cloud-based

Quick start

Installation

# Requires Python 3.8-3.11
pip install -U openai-whisper

# Requires ffmpeg
# macOS: brew install ffmpeg
# Ubuntu: sudo apt install ffmpeg
# Windows: choco install ffmpeg

Basic transcription

import whisper

# Load model
model = whisper.load_model("base")

# Transcribe
result = model.transcribe("audio.mp3")

# Print text
print(result["text"])

# Access segments
for segment in result["segments"]:
    print(f"[{segment['start']:.2f}s - {segment['end']:.2f}s] {segment['text']}")

Model sizes

# Available models
models = ["tiny", "base", "small", "medium", "large", "turbo"]

# Load specific model
model = whisper.load_model("turbo")  # Fastest, good quality

Model	Parameters	English-only	Multilingual	Speed	VRAM
tiny	39M	✓	✓	~32x	~1 GB
base	74M	✓	✓	~16x	~1 GB
small	244M	✓	✓	~6x	~2 GB
medium	769M	✓	✓	~2x	~5 GB
large	1550M	✗	✓	1x	~10 GB
turbo	809M	✗	✓	~8x	~6 GB

Recommendation: Use turbo for best speed/quality, base for prototyping

Transcription options

Language specification

# Auto-detect language
result = model.transcribe("audio.mp3")

# Specify language (faster)
result = model.transcribe("audio.mp3", language="en")

# Supported: en, es, fr, de, it, pt, ru, ja, ko, zh, and 89 more

Read the full file on GitHub · 321 lines

Files

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.

references/languages.md 4.7 KB

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.

2mo ago First seen · 321 lines · 67 tokens per session scan B 060e2cc18ff6

Subscribe to this mod's changes

whisper is a skill published in the GitHub repository Tommy-yw/RunbookHermes (513 stars, last pushed 5mo ago), licensed MIT. It adds 67 tokens to every session and 2,035 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). It is 97% identical to multimodal-whisper, differing in 12 lines, and is treated as a copy.

Data and AI

whisper next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
whisperTommy-yw/RunbookHermes	Skill	513	5mo ago	MIT	B	67	Claude Code, Codex
agent-platform-model-registrygoogle/skills	Skill	24k	today	Apache-2.0	A	60	Claude Code, Codex
llm-evaluationsickn33/agentic-awesome-skills	Skill	50k	today	MIT	A	25	Claude Code
foundry-config-setupmicrosoft/agent-framework	Skill	15k	today	MIT	A	65	Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills	Skill	24k	today	Apache-2.0	A	132	Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	2d ago	MIT	A	35	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	4.0k	today	Apache-2.0	A	30	Claude Code

whisper