Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add krishagel/geoffrey/plugin install geoffreyWrote 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/krishagel/geoffrey/local-tts)<a href="https://agentmods.dev/skills/krishagel/geoffrey/local-tts"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/local-tts/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/krishagel/geoffrey/local-tts"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/local-tts.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 | $0.00016 | $0.01000 |
| Opus 5 | $0.00008 | $0.00500 |
| Sonnet 5 | $0.00003 | $0.00200 |
| Haiku 4.5 | $0.00002 | $0.00100 |
Grade A, and why
local-tts 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- local-tts — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local TTS Skill
Generate high-quality speech audio locally using Apple Silicon MLX acceleration and the Kokoro-82M model. No API keys or recurring costs.
Quick Start
# Generate MP3 from text
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
--text "Hello, this is a test." \
--output ~/Desktop/test.mp3
# Generate from file
uv run --with mlx-audio --with pydub skills/local-tts/scripts/generate_audio.py \
--file /tmp/script.txt \
--voice af_heart \
--output ~/Desktop/podcast.mp3
# List available voices
uv run --with mlx-audio skills/local-tts/scripts/list_voices.py
Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
--text |
One of text/file | - | Text to convert |
--file |
One of text/file | - | Path to text file |
--voice |
No | af_heart |
Voice preset |
--output |
Yes | - | Output file path (.mp3, .wav) |
--model |
No | Kokoro-82M-bf16 |
Model to use |
--list-voices |
No | - | Show available voices |
Voice Presets
American English Female (prefix: af_)
af_heart- Warm, friendly (default)af_bella- Soft, calmaf_nova- Clear, professionalaf_river- Clear, confidentaf_sarah- Soft, expressive
American English Male (prefix: am_)
am_adam- Clear, professionalam_echo- Deep, smootham_liam- Articulate, conversationalam_michael- Soft, measured
British English (prefix: bf_, bm_)
bf_emma- Clear, refined femalebm_daniel- Clear, professional malebm_george- Distinguished male
See references/voices.md for full list.
Output Format
{
"success": true,
"file": "/Users/hagelk/Desktop/podcast.mp3",
"voice": "af_heart",
"model": "Kokoro-82M-bf16",
"characters": 9824,
"chunks": 20,
"duration_seconds": 612.5,
"generation_time": 45.2
}
Performance
| Hardware | Speed | Notes |
|---|---|---|
| M3 Pro 36GB | ~3-4x realtime | First run slower (model loading) |
| M1/M2 Mac Mini 8GB | ~1.5x realtime | Works well for briefings |
| M1/M2 Mac Mini 16GB | ~2x realtime | Comfortable headroom |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 119 lines · 16 tokens per session scan A 75496fff5472
local-tts is a skill published in the GitHub repository krishagel/geoffrey (5 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 1,000 once invoked, about $0.0001 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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