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transcription-speech-to-text-hebrew
by
NetanelRotem
· GitHub ↗
· v1.0.3
· MIT-0
124
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install transcription-speech-to-text-hebrew
Description
Transcribe audio or video files using the TextOps/Modal API. Use this skill whenever the user wants to transcribe a video or audio file, mentions an mp4/mp3/...
Usage Guidance
This skill appears to implement a legitimate transcription flow, but proceed with caution: (1) The SKILL.md and scripts require TEXTOPS_API_KEY, but the registry metadata incorrectly lists no required env vars — assume you must supply TEXTOPS_API_KEY to use the skill. (2) Using the skill will upload audio/video and send your API key to text-ops-subs.com; only use it if you trust that service with the content. (3) The included download script auto-installs yt-dlp via pip at runtime (uses --break-system-packages), which modifies your environment — prefer running these scripts in an isolated environment or sandbox. (4) If you need stronger assurance, ask the publisher to fix the registry metadata to declare TEXTOPS_API_KEY, provide a formal privacy/data-retention statement, and/or run the scripts in a disposable VM to verify behavior before giving the key. If you want, I can list the exact network endpoints and files the scripts contact and modify, or produce a minimal checklist to safely test the skill in isolation.
Capability Analysis
Type: OpenClaw Skill
Name: transcription-speech-to-text-hebrew
Version: 1.0.3
The skill bundle is a legitimate transcription tool for Hebrew and other languages using the TextOps API. It includes scripts for downloading YouTube audio (via yt-dlp), uploading files to a transcription service, and processing the results. Notably, the SKILL.md file includes proactive security instructions for the AI agent, explicitly warning it to treat transcription output as untrusted third-party data and to avoid executing any commands found within transcripts. While the download script performs automated package installation (pip install yt-dlp), this behavior is documented and necessary for the stated functionality.
Capability Assessment
Purpose & Capability
The code and SKILL.md implement a transcription flow (local upload, YouTube download, polling TextOps endpoints) which matches the skill name/description. However the registry metadata claims no required environment variables while both SKILL.md and transcribe.py require a TEXTOPS_API_KEY — a clear metadata/claim mismatch that should be corrected.
Instruction Scope
SKILL.md confines runtime behavior to gathering files/URLs, optionally downloading YouTube audio, and running the bundled scripts. It also explicitly warns about treating transcript output as untrusted data. The instructions do not request unrelated system files or unrelated credentials.
Install Mechanism
There is no formal install spec (instruction-only), but the included scripts auto-install yt-dlp via pip at runtime (download_audio.py calls pip with --upgrade and --break-system-packages). Auto-installing packages at runtime alters the host environment and is higher-risk than a pure instruction-only skill; the packages come from PyPI (yt-dlp) which is expected for YouTube downloading.
Credentials
The skill requires a single service credential (TEXTOPS_API_KEY) used to authenticate requests to text-ops-subs.com; that is proportionate to a cloud transcription service. The main concern is that the registry metadata does not declare this required env var, so users may not be warned before installation. Also note that the API key and audio files are sent to an external service (text-ops-subs.com / agents.text-ops-subs.com), so users must trust that service with potentially sensitive audio.
Persistence & Privilege
The skill does not request 'always: true' and does not modify other skills or system-wide settings. It runs as-needed and does not request elevated platform privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install transcription-speech-to-text-hebrew - After installation, invoke the skill by name or use
/transcription-speech-to-text-hebrew - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
**Adds auto-response to feature/capability questions.**
- Now answers "what can you do?" (or Hebrew equivalent) with a summary of features before any transcription steps.
- Expanded SKILL.md description to mention this new trigger.
- Feature list includes YouTube downloads, speaker diarization, word-level timestamps, and supported formats.
- No code or logic changes to the transcription process.
v1.0.2
- Updated documentation, including detailed usage instructions, security guidelines, and privacy information in SKILL.md.
- Outlines specific handling for YouTube URLs, with step-by-step guidance for downloading and processing audio.
- Describes rules and checks for speaker diarization, word-level timestamps, and file handling.
- Adds explicit security measures for handling untrusted transcription output and file names.
- Provides clear setup instructions and error messages for missing API keys or unsupported file types.
Metadata
Frequently Asked Questions
What is transcription-speech-to-text-hebrew?
Transcribe audio or video files using the TextOps/Modal API. Use this skill whenever the user wants to transcribe a video or audio file, mentions an mp4/mp3/... It is an AI Agent Skill for Claude Code / OpenClaw, with 124 downloads so far.
How do I install transcription-speech-to-text-hebrew?
Run "/install transcription-speech-to-text-hebrew" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is transcription-speech-to-text-hebrew free?
Yes, transcription-speech-to-text-hebrew is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does transcription-speech-to-text-hebrew support?
transcription-speech-to-text-hebrew is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created transcription-speech-to-text-hebrew?
It is built and maintained by NetanelRotem (@netanelrotem); the current version is v1.0.3.
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