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Openai Whisper Api

Checked
steipete·vlatest·ai-ml·MIT

Helps with OpenAI, API as part of building AI and machine learning applications workflows.

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 openclaw/openclaw --skill openai-whisper-api -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

steipete

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

    Only contacts known or declared hosts: api.openai.com.

    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.

    Hosts contacted

    api.openai.commodel provider

  • 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 steipete/clawdis at db197f9a8f.

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

Commit
db197f9a8f
Manifest
skills/openai-whisper-api/SKILL.md
Scanned
2 files, 221 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

The OpenAI Whisper API skill enables AI agents to transcribe audio files into text using OpenAI's robust speech-to-text models. It supports multiple languages and handles various audio formats, making it ideal for processing voice notes, interviews, or recorded meetings directly within an agent workflow.

When to use it

  • Convert spoken language from podcasts or lectures into searchable transcripts for analysis.
  • Extract text from customer support call recordings to populate ticket systems automatically.
  • Transcribe multilingual audio content without needing separate models for each language.
  • Process short voice memos or dictation tasks where high accuracy is required.

Key capabilities

  • Access to OpenAI's Whisper model variants (base, small, medium, large).
  • Support for over 100 languages and dialects.
  • Automatic detection of the spoken language in the audio file.
  • Handling of various audio formats including MP3, WAV, and more.

Example prompts

  • "Transcribe this uploaded audio file into text using the Whisper model."
  • "Detect the language spoken in this recording and provide a full transcript."
  • "Extract all speaker segments from this meeting recording and label them by timestamp."

Tips & gotchas

Ensure your audio files are reasonably clean; excessive background noise may reduce transcription accuracy. Larger models like 'large-v3' offer better precision but require more computational resources and time to process compared to smaller variants.