Skip to content
TrustedSkillsbeta
Back to all skills

Openai Whisper

Checked
thinkfleetai·vlatest·ai-ml

Transcribes audio into text using OpenAI's Whisper model, enabling automated analysis and understanding of spoken content.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add thinkfleetai/thinkfleet-engine --skill openai-whisper -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

thinkfleetai

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned thinkfleetai/thinkfleet-engine at 1256c5192f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
1256c5192f
Manifest
skills/openai-whisper/SKILL.md
Scanned
1 file, 20 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill leverages OpenAI's Whisper model to transcribe audio into text. It can handle various audio formats and languages, providing accurate transcriptions for meetings, lectures, or any spoken content. The resulting transcripts are useful for creating summaries, generating captions, or improving accessibility.

When to use it

  • Meeting Transcription: Automatically generate a written record of team meetings.
  • Lecture Note Taking: Create text-based notes from recorded lectures and presentations.
  • Podcast Summarization: Quickly summarize the key points discussed in podcast episodes.
  • Accessibility for Audio Content: Provide transcripts for audio files to improve accessibility for individuals who are deaf or hard of hearing.

Key capabilities

  • Audio transcription
  • Support for multiple languages
  • Handles various audio file formats

Example prompts

  • "Transcribe this audio file: [audio file]"
  • "What was said in the following recording? [audio file]"
  • “Generate a transcript of this meeting.” [audio file]

Tips & gotchas

  • The accuracy of transcription depends on the quality of the audio input. Clear audio with minimal background noise will yield better results.