Whisper Cpp Local Transcription Engine

Name: Whisper Cpp Local Transcription Engine
Author: agentskillexchange

ASecurity

Runs OpenAI Whisper models locally via whisper.cpp with GGML quantized weights for CPU-efficient transcription. Supports beam search decoding, VAD-based segmentation, and SRT/VTT subtitle output formats.

36 stars
0 votes
0 copies
1 view
Added June 8, 2026

ai-agentspythongobashgitsecurity

Works with

claude code

Security analysis

A92/100

mediumInstalls packages at runtime which could introduce malicious dependencies

Pro shows the line behind each finding and how to fix it

Scanned June 8, 2026

npx -y skills add agentskillexchange/skills --skill whisper-cpp-local-transcription-engine --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Whisper Cpp Local Transcription Engine?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Whisper Cpp Local Transcription Engine

[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/agentskillexchange-whisper-cpp-local-transcription-engine/badge)](https://www.skillsdirectory.com/skills/agentskillexchange-whisper-cpp-local-transcription-engine)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro

SKILL.md

---
name: "Whisper.cpp Local Transcription Engine"
slug: "whisper-cpp-local-transcription-engine"
description: "Runs OpenAI Whisper models locally via whisper.cpp with GGML quantized weights for CPU-efficient transcription. Supports beam search decoding, VAD-based segmentation, and SRT/VTT subtitle output formats."
github_stars: 97775
verification: "security_reviewed"
source: "https://github.com/openai/whisper"
category: "Media & Transcription"
framework: "Claude Code"
tool_ecosystem:
  github_repo: "openai/whisper"
  github_stars: 97775
---

# Whisper.cpp Local Transcription Engine

Runs OpenAI Whisper models locally via whisper.cpp with GGML quantized weights for CPU-efficient transcription. Supports beam search decoding, VAD-based segmentation, and SRT/VTT subtitle output formats.

## Installation

Use the upstream install or setup path that matches your environment:
- pip install -U openai-whisper
- pip install git+https://github.com/openai/whisper.git
- pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git
- brew install ffmpeg

Requirements and caveats from upstream:
- We used Python 3.9.9 and [PyTorch](https://pytorch.org/) 1.10.1 to train and test our models, but the codebase is expected to be compatible with Python 3.8-3.11 and recent PyTorch versions. The codebase also depends o...
- Alternatively, the following command will pull and install the latest commit from this repository, along with its Python dependencies:
- It also requires the command-line tool [ffmpeg](https://ffmpeg.org/) to be installed on your system, which is available from most package managers:

Basic usage or getting-started notes:
- [[Colab example]](https://colab.research.google.com/github/openai/whisper/blob/master/notebooks/LibriSpeech.ipynb)
- To update the package to the latest version of this repository, please run:
- bash

- Source: https://github.com/openai/whisper
- Extracted from upstream docs: https://raw.githubusercontent.com/openai/whisper/HEAD/README.md

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/whisper-cpp-local-transcription-engine/)