Agent skill · creative production · davila7
speech
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation. OpenAI remains the default; Atlas Cloud is an explicit optional backend for asynchronous multilingual speech. Custom voice creation is out of scope.
Why this skill is useful
Adds a structured workflow for generating text-to-speech audio with specific commands and API integration that the AI wouldn't reliably generate on its own.
What it needs
Requires openai, uv installed locally. Requires openai account access. About 4k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
Speech Generation Skill Generate spoken audio for the current project (narration, product demo voiceover, IVR prompts, accessibility reads). OpenAI remains the default with gpt-4o-mini-tts-2025-12-15; Atlas Cloud is available only when the user explicitly selects it. Prefer the bundled CLIs 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 scripts/texttospeech.py for the default OpenAI path, or scripts/atlastexttospeech.py only when Atlas Cloud was selected (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. OpenAI backend package: If uv is unavailable: The Atlas Cloud backend uses only the Python standard library. Environment Default OpenAI calls require OPENAIAPIKEY. Optional Atlas Cloud calls require ATLASCLOUDAPIKEY. If the selected provider key is missing, give the user these steps: 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/speech