Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
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Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
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Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
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Provides ASR (Automatic Speech Recognition) services via uwebasr.zcu.cz. Use this skill to transcribe audio files in multiple languages (CS, SK, EN, DE, PL, HU, HR, SR, NL) using state-of-the-art models like Zipformer.
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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
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High-quality voice synthesis with 18 personas, 32 languages, sound effects, batch processing, and voice design using ElevenLabs API.
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Text-to-speech conversion using node-edge-tts npm package for generating audio from text. Supports multiple voices, languages, speed adjustment, pitch control, and subtitle generation. Use when: (1) User requests audio/voice output with the "tts" trigger or keyword. (2) Content needs to be spoken rather than read (multitasking, accessibility, driving, cooking). (3) User wants a specific voice, speed, pitch, or format for TTS output.
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Build backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.
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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Turn an article, doc or release note into a short explainer clip — one person to camera, or a voiceover over illustrative footage. The user supplies the source text and the model generates the speech; audio cannot be uploaded, measured. A 30-second clip holds about eighty spoken words in eight sentences — measured, and well under a tenth of a 1,200-word post — so this skill does not summarise an article, it picks the single idea worth saying and helps choose which one. Use when a user asks to turn writing into a short spoken video, e.g. "make a 30-second explainer from this blog post", "explain this feature in a short video", "turn our changelog into a clip", "a quick video explaining what this paper found". Do not use for a scene between people (see seedance-short-drama), a brand or product ad (see seedance-ad-creative), a handheld creator clip (see ugc-ads), or when the user already has both a portrait and the finished words (see talking-head). Budget sentences as well as words — each sentence boundary costs about 0.7 seconds of silence, so a script with more sentences runs longer at the same word count.
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