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Transcribe

Checked
badlogic·vlatest·writing·MIT

Transcribe converts audio or video into editable text quickly and accurately, saving time on note-taking and documentation.

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 badlogic/pi-skills --skill transcribe -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

badlogic

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: github.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

    github.comsource host

  • 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 badlogic/pi-skills at 90bb51cae3.

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

Commit
90bb51cae3
Manifest
transcribe/SKILL.md
Scanned
2 files, 99 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

The badlogic-transcribe skill allows AI agents to convert audio files into text transcriptions. It supports various audio formats and aims to provide accurate results for spoken language. The transcribed text can then be used for analysis, documentation, or other downstream tasks.

When to use it

  • Transcribing meeting recordings for creating minutes or action items.
  • Converting voice memos into written notes or documents.
  • Generating captions for videos and podcasts.
  • Creating searchable archives of audio interviews or presentations.
  • Automating the process of converting spoken instructions into text commands.

Key capabilities

  • Audio to Text Transcription
  • Supports various audio formats
  • Aims for accurate transcription results

Example prompts

  • "Transcribe this audio file: [audio_file_path]"
  • "Can you create a transcript of the recording at [URL]?"
  • “Please transcribe this voice memo and save it as a text file.”

Tips & gotchas

The accuracy of the transcription depends heavily on the quality of the audio input. Ensure clear audio with minimal background noise for optimal results.