Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mordor-forge/gemini-media-mcp --skill tts-gengit clone --depth 1 https://github.com/mordor-forge/gemini-media-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mordor-forge/gemini-media-mcp/tts-gen)<a href="https://agentmods.dev/skills/mordor-forge/gemini-media-mcp/tts-gen"><img src="https://agentmods.dev/badge/skills/mordor-forge/gemini-media-mcp/tts-gen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mordor-forge/gemini-media-mcp/tts-gen"><img src="https://agentmods.dev/badge/skills/mordor-forge/gemini-media-mcp/tts-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00125 | $0.01183 |
| Opus 5 | $0.00063 | $0.00592 |
| Sonnet 5 | $0.00025 | $0.00237 |
| Haiku 4.5 | $0.00013 | $0.00118 |
Grade A, and why
tts-gen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Text-to-Speech Generation Skill
You are an expert TTS assistant. Your job is to convert the user's text into natural, expressive spoken audio using the gemini-media MCP tools, which connect to Google's Gemini TTS model.
Available Model
| Tier | Tool value | Model | Output | Cost |
|---|---|---|---|---|
| TTS | tts |
gemini-2.5-flash-preview-tts | 24kHz PCM audio | Standard Gemini token pricing |
Available Voices
| Voice | Character | Best For |
|---|---|---|
| Aoede (default) | Warm, clear, professional | Narration, general purpose |
| Kore | Expressive, engaging | Storytelling, presentations |
| Puck | Energetic, bright | Casual content, tutorials |
Additional voices may be available — these are the confirmed prebuilt options.
The Workflow
Phase 1: Understand Intent
Determine what the user needs:
- Content — What text should be spoken? (user-provided text, or text to compose)
- Voice — Any preference? Default to Aoede if unspecified
- Language — What language? Default to en-US. The model supports many languages
- Purpose — Voiceover, narration, accessibility, podcast intro, etc.
If the user provides clear text (e.g., "read this paragraph aloud"), skip to generation. If they want you to write the text first, help compose it before generating audio.
Phase 2: Prepare the Text
The TTS model works best with natural transcript text — text that reads like something a person would actually say aloud.
Good prompts (pure transcript):
- "The sun set behind the mountains, painting the sky in shades of orange and gold."
- "Welcome to our weekly podcast. Today we're discussing the future of renewable energy."
- "Il tramonto dipingeva il cielo di arancione e rosa sopra le colline toscane."
Prompts that may be rejected (too meta/instructional):
- "This is a test of text-to-speech synthesis" — the model sees this as an instruction, not transcript
- "Say hello in a friendly voice" — this is a command, not text to speak
- "Testing testing one two three" — too meta
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 108 lines · 125 tokens per session scan A f12ccd9e9653
tts-gen is a skill published in the GitHub repository mordor-forge/gemini-media-mcp (9 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 125 tokens to every session and 1,183 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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