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Official agent skill

Speech

by JetBrains in JetBrains/skills

A skill your agent uses 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…

OfficialApache-2.0Auto-check passedMedia & Creative

Install Speech

skills CLI
$ npx skills add JetBrains/skills --skill speech -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install JetBrains/skills speech --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/JetBrains/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/speech .claude/skills/speech && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
speech
GitHub stars
364
Used in
4 other repos
Token cost
~1.9k tokens
SKILL.md length
756 words
Files
16 (incl. scripts, references, assets)
Skills in repo
77
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses 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…

  • Works in 8 steps: Decide intent: single vs batch (see… → Collect inputs up front: exact text… → If batch: write a temporary JSONL under… → …
  • The user asks for text-to-speech narration
  • SKILL.md covers When to use, Decision tree (single vs batch), Workflow and Temp and output conventions, plus 9 more sections
  • Runs Python scripts from its folder; calls uv and python3; needs OPENAI_API_KEY

What it does

Speech is an agent skill from JetBrains/skills, published by the product's own GitHub organization. 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/texttospeech.py) with built-in voices and require OPENAIAPIKEY for live calls. Custom voice creation is out of scope.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `references/accessibility.md` and `references/audio-api.md`).

It sits in Media & Creative, covering Text to speech and voice. It works with OpenAI. The repository describes itself as: Curated agent skills collection verified by JetBrains. The licence is Apache-2.0.

When your agent uses it

  • The user asks for text-to-speech narration
  • Accessibility reads
  • Batch speech generation via the OpenAI Audio API
  • Run the bundled CLI (scripts/texttospeech.py) with built-in voices and require OPENAIAPIKEY for live calls

Example prompts

  • “/speech”

Requirements

  • Python 3
  • A credential in OPENAI_API_KEY

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit e0f258b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • platform.openai.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Speech loads about 1.9k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 756 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from JetBrains/skills at commit e0f258b, republished under its Apache-2.0 licence (© JetBrains). 756 words, ~1,851 tokens.

Download SKILL.mdSave it as .claude/skills/speech/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
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.
metadata.short-description
Generate narrated audio from text
metadata.author
OpenAI
metadata.source
https://github.com/openai/skills/tree/main/skills/.curated/speech

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 packages:

uv pip install openai

If uv is unavailable:

python3 -m pip install openai

Environment

  • OPENAI_API_KEY must be set for live API calls.

If the key is missing, give the user these steps:

  1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys
  2. Set OPENAI_API_KEY as an environment variable in their system.
  3. Offer to guide them through setting the environment variable for their OS/shell if needed.
  • Never ask the user to paste the full key in chat. Ask them to set it locally and confirm when ready.

If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally.

Defaults & rules

  • Use gpt-4o-mini-tts-2025-12-15 unless the user requests another model.
  • Default voice: cedar. If the user wants a brighter tone, prefer marin.
  • Built-in voices only. Custom voices are out of scope for this skill.
  • instructions are supported for GPT-4o mini TTS models, but not for tts-1 or tts-1-hd.
  • Input length must be <= 4096 characters per request. Split longer text into chunks.
  • Enforce 50 requests/minute. The CLI caps --rpm at 50.
  • Require OPENAI_API_KEY before any live API call.
  • Provide a clear disclosure to end users that the voice is AI-generated.
  • Use the OpenAI Python SDK (openai package) for all API calls; do not use raw HTTP.
  • Prefer the bundled CLI (scripts/text_to_speech.py) over writing new one-off scripts.
  • Never modify scripts/text_to_speech.py. If something is missing, ask the user before doing anything else.
Show full SKILL.md (300 more words)Show less

Instruction augmentation

Reformat user direction into a short, labeled spec. Only make implicit details explicit; do not invent new requirements.

Quick clarification (augmentation vs invention):

  • If the user says "narration for a demo", you may add implied delivery constraints (clear, steady pacing, friendly tone).
  • Do not introduce a new persona, accent, or emotional style the user did not request.

Template (include only relevant lines):

Voice Affect: <overall character and texture of the voice>
Tone: <attitude, formality, warmth>
Pacing: <slow, steady, brisk>
Emotion: <key emotions to convey>
Pronunciation: <words to enunciate or emphasize>
Pauses: <where to add intentional pauses>
Emphasis: <key words or phrases to stress>
Delivery: <cadence or rhythm notes>

Augmentation rules:

  • Keep it short; add only details the user already implied or provided elsewhere.
  • Do not rewrite the input text.
  • If any critical detail is missing and blocks success, ask a question; otherwise proceed.

Examples

Single example (narration)
Input text: "Welcome to the demo. Today we'll show how it works."
Instructions:
Voice Affect: Warm and composed.
Tone: Friendly and confident.
Pacing: Steady and moderate.
Emphasis: Stress "demo" and "show".
Batch example (IVR prompts)
{"input":"Thank you for calling. Please hold.","voice":"cedar","response_format":"mp3","out":"hold.mp3"}
{"input":"For sales, press 1. For support, press 2.","voice":"marin","instructions":"Tone: Clear and neutral. Pacing: Slow.","response_format":"wav"}

Instructioning best practices (short list)

  • Structure directions as: affect -> tone -> pacing -> emotion -> pronunciation/pauses -> emphasis.
  • Keep 4 to 8 short lines; avoid conflicting guidance.
  • For names/acronyms, add pronunciation hints (e.g., "enunciate A-I") or supply a phonetic spelling in the text.
  • For edits/iterations, repeat invariants (e.g., "keep pacing steady") to reduce drift.
  • Iterate with single-change follow-ups.

More principles: references/prompting.md. Copy/paste specs: references/sample-prompts.md.

Guidance by use case

Use these modules when the request is for a specific delivery style. They provide targeted defaults and templates.

  • Narration / explainer: references/narration.md
  • Product demo / voiceover: references/voiceover.md
  • IVR / phone prompts: references/ivr.md
  • Accessibility reads: references/accessibility.md

CLI + environment notes

  • CLI commands + examples: references/cli.md
  • API parameter quick reference: references/audio-api.md
  • Instruction patterns + examples: references/voice-directions.md
  • If network approvals / sandbox settings are getting in the way: references/codex-network.md

Reference map

  • references/cli.md: how to run speech generation/batches via scripts/text_to_speech.py (commands, flags, recipes).
  • references/audio-api.md: API parameters, limits, voice list.
  • references/voice-directions.md: instruction patterns and examples.
  • references/prompting.md: instruction best practices (structure, constraints, iteration patterns).
  • references/sample-prompts.md: copy/paste instruction recipes (examples only; no extra theory).
  • references/narration.md: templates + defaults for narration and explainers.
  • references/voiceover.md: templates + defaults for product demo voiceovers.
  • references/ivr.md: templates + defaults for IVR/phone prompts.
  • references/accessibility.md: templates + defaults for accessibility reads.
  • references/codex-network.md: environment/sandbox/network-approval troubleshooting.

© JetBrains, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 15 other files (scripts, references, assets) in speech of JetBrains/skills.

  • SKILL.md
  • LICENSE.txt
  • agents/openai.yaml
  • assets/speech-small.svg
  • assets/speech.png
  • references/accessibility.md
  • references/audio-api.md
  • references/cli.md
  • references/codex-network.md
  • references/ivr.md
  • references/narration.md
  • references/prompting.md
  • references/sample-prompts.md
  • references/voice-directions.md
  • references/voiceover.md
  • scripts/text_to_speech.py

Open the folder on GitHubat commit e0f258b

Used in 4 other repositories

We found 16 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in JetBrains/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Speech next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Speech compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Speech this skillJetBrains/skills3644 repos~1.9kAutomated safety check: PassApache-2.0
Podcastteam-attention/plugins-for-claude-natives827—~1.5kAutomated safety check: PassMIT
Voxclawmalpern/VoxClaw208—~1.9kAutomated safety check: PassNone
Lessongug007/lpm152—~1.2kAutomated safety check: PassMIT
Speechdavila7/claude-code-templates32k—~2kAutomated safety check: PassApache-2.0
Speechnexu-io/open-design100k—~291Automated safety check: PassApache-2.0

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Works with

Categories

Questions about Speech

What does Speech do?

A skill your agent uses 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…. Speech is an agent skill from JetBrains/skills, published by the product's own GitHub organization.py) with built-in voices and require OPENAIAPIKEY for live calls.

When should I use Speech?

Speech fits situations like: the user asks for text-to-speech narration; accessibility reads; batch speech generation via the OpenAI Audio API; run the bundled CLI (scripts/texttospeech.py) with built-in voices and require OPENAIAPIKEY for live calls.

How do I install Speech in Claude Code?

Run `npx skills add JetBrains/skills --skill speech -a claude-code`. Or copy the skill folder (speech in JetBrains/skills) into .claude/skills/speech in your project. Claude Code loads it when a task matches its description.

How do I install Speech in Codex?

Run `npx skills add JetBrains/skills --skill speech -a codex`. Or copy the skill folder (speech in JetBrains/skills) into .agents/skills/speech in your project. Codex loads it when a task matches its description.

Can I use Speech in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add JetBrains/skills --skill speech -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/speech, .gemini/skills/speech, .github/skills/speech and .opencode/skills/speech in your project.

What does Speech need to run?

Going by SKILL.md and its folder, Speech needs Python for the scripts in its folder, the command-line tools its instructions call (uv and python3) and credentials named OPENAI_API_KEY. Our summary lists: Python 3; A credential in OPENAI_API_KEY.

Does Speech access the network?

SKILL.md names 1 domain. As links in the text: platform.openai.com. This is read from the text; nothing was executed.

Is Speech safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Speech use?

Speech is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Speech use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.2k tokens, read only when the agent opens those files.

What are the alternatives to Speech?

Skills that share tags, products or a category with Speech: Podcast (team-attention/plugins-for-claude-natives, 827 stars), Voxclaw (malpern/VoxClaw, 208 stars), Lesson (gug007/lpm, 152 stars) and Speech (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Speech?

JetBrains (a GitHub organization, an official publisher) maintains it in JetBrains/skills, which has 364 GitHub stars. The repository holds 77 skills in this directory. The repository was last updated on June 29, 2026.

Source: JetBrains/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.