gemini-tts
Skill396 starsChanged 6 months agoMITView on GitHub
Render text to mp3 via Google Gemini Flash TTS. Free-tier eligible (1500 req/day). Use for video narration, demo voiceovers, audio notes. Parallels openai-tts; default for make-viral-video.
- Reads credentials
5 other projects use a version of this.
Adopted by
Most recently taken up by
- akrindev/google-studio-skillstheir own version, first seen Nov 8, 2026
- iurysza/agent-skillstheir own version, first seen Nov 1, 2026
- brandonbryant12/clearframetheir own version, first seen Oct 20, 2026
- memex-lab/product-launch-video-skilltheir own version, first seen Jun 1, 2026
- Panastra-labs/skillstheir own version, first seen Mar 4, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- memex-lab/product-launch-video-skill★ 12same name
- akrindev/google-studio-skills★ 7same name
- iurysza/agent-skills★ 5same name
- brandonbryant12/clearframe★ 1same name
- Panastra-labs/skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository73 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- agent-activitySkill
- agent-registrySkill
- agent-room-opsSkill
- answer-formatSkill
- audio-transcribeSkill
- bee-actionsSkill
- bot2bot-postSkill
- call-diagnosticsSkill
- claude-codexSkill
- claude-geminiSkill
- claude-piSkill
- claude-routerSkill
- collaboration-intelligenceSkill
- connect-appsSkill
- context-dropSkill
- context-reconstructSkill
- db-browserSkill
- deal-finderSkill
- doc-ingestSkill
- electron-overlay-dimmingSkill
- email-findSkill
- engine-conflict-resolveSkill
- image-generationSkill
- import-claude-contextSkill
- local-workspace-serverSkill
- macos-toolsSkill
- macos-useSkill
- make-viral-videoSkill
- marketplaceSkill
- media-transcriptSkill
- meeting-prepSkill
- meeting-schedulerSkill
- mention-gateSkill
- model-switchSkill
- morning-briefingSkill
- ms365-connectSkill
- observeSkill
- obsidian-vaultSkill
- openai-ttsSkill
- open-sutando-refSkill
- overlay-appsSkill
- phone-conversationSkill
- proactive-loopSkill
- pr-shepherd-contractSkill
- quota-trackerSkill
- regression-searchSkill
- relaySkill
- releaseSkill
- report-feedbackSkill
- review-preflightSkill
- room-collabSkill
- schedule-cronsSkill
- screen-companionSkill
- screen-recordSkill
- self-diagnoseSkill
- self-upgradeSkill
- session-recapSkill
- skill-usage-reportSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 31
Default: gemini-2.5-flash-preview-tts (free tier, 1500 req/day, $0 within quota).
- Very specific: line 46
Default output path: results/gemini-tts-{epoch}.mp3.
- Distinctive: line 65
If ARGUMENTS is empty, ask the user for the text.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Gemini TTS
Synthesize speech via Google's gemini-2.5-flash-preview-tts (or -pro-tts / -lite-preview-tts per env override). Reads GEMINI_API_KEY from .env.
This is offline synthesis — distinct from voice-agent's bidirectional Gemini Live audio. Same model family, different surface (POST text → get audio bytes back, no streaming).
Usage: /gemini-tts [text]
ARGUMENTS: $ARGUMENTS
Voices
Aoede (default — alto, neutral), Charon (baritone, news-anchor), Kore (mid, expressive), Puck (high, conversational). Per Lucy's 2026-05-09 testing: Aoede is the closest match to OpenAI's sage.
Audio tags for expression
Inline bracket tags like [whispers], [excitedly], [slowly] are interpreted as stylistic direction, not spoken literally. Empirically verified against gemini-2.5-flash-preview-tts (per PR #646 comment): [whispers] hello → 1.05s audio; hello alone → 1.01s. If the tag were spoken literally as 8 words, the clip would be ~5× longer.
bash "$SKILL_DIR/scripts/synthesize.sh" -- "[whispers] Pull request 691 has landed."Model selection
Default: gemini-2.5-flash-preview-tts (free tier, 1500 req/day, $0 within quota).
Override via GEMINI_TTS_MODEL env var:
gemini-2.5-pro-tts— paid, higher fidelitygemini-2.5-flash-lite-preview-tts— preview, fastergemini-3.1-flash-tts-preview— preview
Examples
bash "$SKILL_DIR/scripts/synthesize.sh" -- "Hello, this is Sutando."
bash "$SKILL_DIR/scripts/synthesize.sh" --voice Charon --out /tmp/intro.mp3 -- "Hi."
GEMINI_TTS_MODEL=gemini-2.5-pro-tts bash "$SKILL_DIR/scripts/synthesize.sh" -- "High-fidelity narration."Default output path: results/gemini-tts-{epoch}.mp3.
Cost
Free tier: $0 within 1500 req/day quota. For our cadence (a few demos a day), stays free indefinitely. Paid (Flash): $0.50 / 1M input tokens + $10.00 / 1M output tokens.
Compared to OpenAI TTS (gpt-4o-mini-tts) at ~$0.02 per 60s: Gemini Flash is free-equivalent for typical demo workloads.
When to fall back to openai-tts
The make-viral-video skill auto-falls-back to OpenAI TTS when:
- Gemini API returns 4xx/5xx
- Gemini quota hit (429)
GEMINI_API_KEYmissingTTS_PROVIDER=OPENAIenv override set
If Invoked As A Slash Command
If ARGUMENTS is empty, ask the user for the text. Otherwise:
bash "$SKILL_DIR/scripts/synthesize.sh" -- "$ARGUMENTS"Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

