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Transcribe

ASecurity

Turn a local audio or video file, or a YouTube link, into a checked transcript and a processed note with Groq Whisper. Use when the person asks to "transcribe this", "what does this recording say", "turn this voice memo into a note", "make subtitles", or another skill needs text from speech.

  • 3 stars
  • 0 votes
  • 0 copies
  • 2 views
  • Added October 10, 2026
ai-agents

Works with

  • cli

Security analysis

A100/100

Pro scans all 7 files and shows the line behind each finding

Scanned October 10, 2026

npx -y skills add ExarLabs/paros-advisor --skill transcribe --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: transcribe
description: Turn a local audio or video file, or a YouTube link, into a checked transcript and a processed note with Groq Whisper. Use when the person asks to "transcribe this", "what does this recording say", "turn this voice memo into a note", "make subtitles", or another skill needs text from speech.
---

# transcribe

Thin entry (PAROS P04). The knowledge lives in a live definition; this file only finds it.

1. Locate the live definition, first match wins:
   - where the vault entry file (`AGENTS.md` or `CLAUDE.md`) says skills live: `<skills folder>/transcribe/CURRENT.md`;
   - `<vault>/PAROS/skills/transcribe/CURRENT.md`;
   - the PAROS reference copy: `<paros repo>/skills/transcribe/CURRENT.md`.
2. Read it in full, and the `LOCAL.md` next to it if present. Read its `version:` field.
3. Report one line before working:
   - from the vault: `Running transcribe v<X> from your vault`;
   - from the reference copy: `Running transcribe v<X> from the PAROS reference, not yet adopted`.
4. Follow it. The client is `transcribe.py` in the same folder. Its `## Constitution` always wins.
5. If the person corrects the result, write a learning packet to the skill's `observations/` folder (P05).

Files in this skill

  • CHANGELOG.md1.5 KB
  • CURRENT.md8.9 KB
  • LOCAL.example.md1.9 KB
  • SKILL.md1.2 KB
  • golden/accepted-output.md1.5 KB
  • golden/input.md1.3 KB
  • transcribe.py16.2 KB

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