Local speech-to-text transcription using OpenAI's Whisper CLI without API keys.
Works with
Transcribes audio files (MP3, M4A, and other formats) directly on your machine with no external API calls required
Supports multiple model sizes (tiny, base, small, medium, large, turbo) with automatic caching to ~/.cache/whisper on first run
Offers transcription and translation tasks with configurable output formats (TXT, SRT, JSON, VTT)
Requires only the whisper CLI binary, installable via Homebrew o
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenai-whisperExecute the skills CLI command in your project's root directory to begin installation:
Fetches openai-whisper from steipete/clawdis and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate openai-whisper. Access via /openai-whisper in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
steipete/clawdis
steipete/clawdis
steipete/clawdis
davila7/claude-code-templates
intellectronica/agent-skills
am-will/codex-skills
Keeps context tight: openai-whisper is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend openai-whisper for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for openai-whisper matched our evaluation — installs cleanly and behaves as described in the markdown.
openai-whisper reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in openai-whisper — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added openai-whisper from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
openai-whisper is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
openai-whisper reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: openai-whisper is focused, and the summary matches what you get after install.
openai-whisper has been reliable in day-to-day use. Documentation quality is above average for community skills.
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