Transcribe audio to text via inference.sh CLI.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionspeech-to-textExecute the skills CLI command in your project's root directory to begin installation:
Fetches speech-to-text from inference-sh/skills 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 speech-to-text. Access via /speech-to-text 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
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Transcribe audio to text via inference.sh CLI.
Requires inference.sh CLI (
infsh). Install instructions
infsh login
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://audio.mp3"}'
| Model | App ID | Best For |
|---|---|---|
| ElevenLabs Scribe v2 | elevenlabs/stt |
98%+ accuracy, diarization, 90+ languages |
| Fast Whisper V3 | infsh/fast-whisper-large-v3 |
Fast transcription |
| Whisper V3 Large | infsh/whisper-v3-large |
Highest accuracy |
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://meeting.mp3"}'
infsh app sample infsh/fast-whisper-large-v3 --save input.json
# {
# "audio_url": "https://podcast.mp3",
# "timestamps": true
# }
infsh app run infsh/fast-whisper-large-v3 --input input.json
infsh app run infsh/whisper-v3-large --input '{
"audio_url": "https://french-audio.mp3",
"task": "translate"
}'
# Extract audio from video first
infsh app run infsh/video-audio-extractor --input '{"video_url": "https://video.mp4"}' > audio.json
# Transcribe the extracted audio
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "<audio-url>"}'
# 1. Transcribe video audio
infsh app run infsh/fast-whisper-large-v3 --input '{
"audio_url": "https://video.mp4",
"timestamps": true
}' > transcript.json
# 2. Use transcript for captions
infsh app run infsh/caption-videos --input '{
"video_url": "https://video.mp4",
"captions": "<transcript-from-step-1>"
}'
Whisper supports 99+ languages including: English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, Hindi, Russian, and many more.
Returns JSON with:
text: Full transcriptionsegments: Timestamped segments (if requested)language: Detected language# ElevenLabs STT (98%+ accuracy, diarization)
npx skills add inference-sh/skills@elevenlabs-stt
# ElevenLabs TTS (reverse direction)
npx skills add inference-sh/skills@elevenlabs-tts
# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@infsh-cli
# Text-to-speech (reverse direction)
npx skills add inference-sh/skills@text-to-speech
# Video generation (add captions)
npx skills add inference-sh/skills@ai-video-generation
# AI avatars (lipsync with transcripts)
npx skills add inference-sh/skills@ai-avatar-video
Browse all audio apps: infsh app list --category audio
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
I recommend speech-to-text for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in speech-to-text — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.
We added speech-to-text from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
speech-to-text fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.
speech-to-text has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: speech-to-text is the kind of skill you can hand to a new teammate without a long onboarding doc.
speech-to-text has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.
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