speech

--- name: "speech" description: "Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope." --- # Speech Generation Skill Generate spoken audio for the current project (narration, product demo voiceover, IVR prompts, accessibility reads). Defaults to `gpt-4o-mini-tts-2025-12-15` and built-in voices, and prefers the bundled CLI for deterministic, reproducible runs. ## When to use - Generate a single spoken clip from text - Generate a batch of prompts (many lines, many files) ## Decision tree (single vs batch) - If the user provides multiple lines/prompts or wants many outputs -> **batch** - Else -> **single** ## Workflow 1. Decide intent: single vs batch (see decision tree above). 2. Collect inputs up front: exact text (verbatim), desired voice, delivery style, format, and any constraints. 3. If batch: write a temporary JSONL under tmp/ (one job per line), run once, then delete the JSONL. 4. Augment instructions into a short labeled spec without rewriting the input text. 5. Run the bundled CLI (`scripts/text_to_speech.py`) with sensible defaults (see references/cli.md). 6. For important clips, validate: intelligibility, pacing, pronunciation, and adherence to constraints. 7. Iterate with a single targeted change (voice, speed, or instructions), then re-check. 8. Save/return final outputs and note the final text + instructions + flags used. ## Temp and output conventions - Use `tmp/speech/` for intermediate files (for example JSONL batches); delete when done. - Write final artifacts under `output/speech/` when working in this repo. - Use `--out` or `--out-dir` to control output paths; keep filenames stable and descriptive. ## Dependencies (install if missing) Prefer `uv` for dependency management. Python package [... prompt truncated for preview ...]