From assemblyai-pack
Transcribes audio/video files via AssemblyAI SDK with speaker diarization, sentiment analysis, entity detection, PII redaction, and content moderation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/assemblyai-pack:assemblyai-core-workflow-aThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Primary money-path workflow: submit audio for async transcription with audio intelligence features. The SDK handles file upload (for local files), queues the transcription job, and polls until completion.
Primary money-path workflow: submit audio for async transcription with audio intelligence features. The SDK handles file upload (for local files), queues the transcription job, and polls until completion.
assemblyai package installedASSEMBLYAI_API_KEYimport { AssemblyAI } from 'assemblyai';
const client = new AssemblyAI({
apiKey: process.env.ASSEMBLYAI_API_KEY!,
});
// Remote URL — SDK queues and polls automatically
const transcript = await client.transcripts.transcribe({
audio: 'https://example.com/meeting-recording.mp3',
});
console.log(transcript.text);
console.log(`Duration: ${transcript.audio_duration}s`);
console.log(`Words: ${transcript.words?.length}`);
// The SDK uploads the file and transcribes in one call
const transcript = await client.transcripts.transcribe({
audio: './recordings/interview.wav',
});
// Or from a buffer/stream
import fs from 'fs';
const buffer = fs.readFileSync('./recordings/interview.wav');
const transcript2 = await client.transcripts.transcribe({
audio: buffer,
});
const transcript = await client.transcripts.transcribe({
audio: audioUrl,
speaker_labels: true,
speakers_expected: 3, // Optional: hint for expected speaker count
});
// Utterances are grouped by speaker
for (const utterance of transcript.utterances ?? []) {
console.log(`Speaker ${utterance.speaker}: ${utterance.text}`);
// Speaker A: Good morning, thanks for joining.
// Speaker B: Happy to be here.
}
const transcript = await client.transcripts.transcribe({
audio: audioUrl,
// Speaker identification
speaker_labels: true,
// Content analysis
sentiment_analysis: true,
entity_detection: true,
auto_highlights: true,
iab_categories: true, // Topic detection (IAB taxonomy)
content_safety: true, // Flag sensitive content
summarization: true,
summary_model: 'informative',
summary_type: 'bullets',
// Formatting
punctuate: true,
format_text: true,
language_code: 'en',
// Word boost for domain terms
word_boost: ['AssemblyAI', 'LeMUR', 'transcription'],
boost_param: 'high',
});
// --- Access results ---
// Sentiment per sentence
for (const s of transcript.sentiment_analysis_results ?? []) {
console.log(`[${s.sentiment}] ${s.text}`);
// [POSITIVE] I really enjoyed working on this project.
}
// Named entities
for (const e of transcript.entities ?? []) {
console.log(`${e.entity_type}: ${e.text}`);
// person_name: John Smith
// location: San Francisco
}
// Auto-highlighted key phrases
for (const h of transcript.auto_highlights_result?.results ?? []) {
console.log(`"${h.text}" (count: ${h.count}, rank: ${h.rank})`);
}
// IAB content categories
const categories = transcript.iab_categories_result?.summary ?? {};
for (const [category, relevance] of Object.entries(categories)) {
if ((relevance as number) > 0.5) {
console.log(`Topic: ${category} (${((relevance as number) * 100).toFixed(0)}%)`);
}
}
// Content safety labels
for (const result of transcript.content_safety_labels?.results ?? []) {
for (const label of result.labels) {
console.log(`Safety: ${label.label} (${(label.confidence * 100).toFixed(0)}%)`);
}
}
// Summary
console.log('Summary:', transcript.summary);
const transcript = await client.transcripts.transcribe({
audio: audioUrl,
redact_pii: true,
redact_pii_policies: [
'email_address',
'phone_number',
'person_name',
'credit_card_number',
'social_security_number',
'date_of_birth',
],
redact_pii_sub: 'hash', // Replace PII with hash. Options: 'hash' | 'entity_name'
redact_pii_audio: true, // Also generate redacted audio file
});
// Text has PII replaced: "My name is ####" or "My name is [PERSON_NAME]"
console.log(transcript.text);
// Get redacted audio URL (takes extra processing time)
if (transcript.redact_pii_audio_quality) {
const redactedAudio = await client.transcripts.redactedAudio(transcript.id);
console.log('Redacted audio URL:', redactedAudio.redacted_audio_url);
}
// List recent transcripts
const page = await client.transcripts.list({ limit: 20 });
for (const t of page.transcripts) {
console.log(`${t.id} | ${t.status} | ${t.audio_duration}s`);
}
// Get a specific transcript
const existing = await client.transcripts.get('transcript-id');
// Delete a transcript (GDPR compliance)
await client.transcripts.delete('transcript-id');
MP3, WAV, FLAC, M4A, OGG, WebM, MP4, AAC. Max file size: 5 GB. Max duration: 10 hours (async). The SDK auto-detects format.
speaker_labels: true)| Error | Cause | Solution |
|---|---|---|
transcript.status === 'error' | Corrupted audio or unsupported format | Verify audio file plays locally |
download_url must be accessible | Private/expired URL | Use a publicly accessible URL or upload locally |
Could not process audio | File too short (<200ms) or silent | Ensure audio has speech content |
word_boost has no effect | Misspelled terms or wrong model | Check spelling; word boost works with Best model tier |
For real-time streaming transcription, see assemblyai-core-workflow-b.
For LLM-powered analysis of transcripts, see assemblyai-sdk-patterns (LeMUR examples).
npx claudepluginhub ia23a-lachnita/claude-code-plugins-plus-fix-skills --plugin assemblyai-pack5plugins reuse this skill
First indexed Jul 10, 2026
Execute AssemblyAI primary workflow: async transcription with audio intelligence. Use when transcribing audio/video files, enabling speaker diarization, sentiment analysis, entity detection, PII redaction, or content moderation. Trigger with phrases like "assemblyai transcribe", "assemblyai transcription", "transcribe audio", "speaker diarization assemblyai".
Implement audio data handling best practices for Deepgram integrations. Use when managing audio file storage, implementing data retention, or ensuring GDPR/HIPAA compliance for transcription data. Trigger: "deepgram data", "audio storage", "transcription data", "deepgram GDPR", "deepgram HIPAA", "deepgram privacy", "PII redaction".
Transcribes audio/video to speaker-labeled text (default) using Qwen3-ASR, Whisper word timings, and pyannote diarization. Local MLX on Apple Silicon or remote API.