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 malue-ai/dazee-small --skill kokoro-ttsgit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/kokoro-tts)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/kokoro-tts"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/kokoro-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/malue-ai/dazee-small/kokoro-tts"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/kokoro-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 | $0.00026 | $0.00569 |
| Opus 5 | $0.00013 | $0.00284 |
| Sonnet 5 | $0.00005 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
kokoro-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.
What it actually says
Kokoro TTS 本地语音合成
使用 Kokoro TTS 引擎在本地生成高质量语音，零 API 成本，完全离线。
使用场景
- 用户说「把这段文字读出来」「生成这篇文章的语音版本」
- 需要将文档、邮件、新闻转为音频
- 优先于 sag（ElevenLabs，需 API Key 和付费）
前置条件
pip install kokoro-onnx soundfile
首次使用需下载模型文件（约 300MB）。
执行方式
基本用法
from kokoro_onnx import Kokoro
kokoro = Kokoro("kokoro-v1.0.onnx", "voices-v1.0.bin")
samples, sample_rate = kokoro.create(
"你好，这是一段测试语音。",
voice="af_heart",
speed=1.0,
lang="z", # z=中文, e=英文
)
import soundfile as sf
sf.write("output.wav", samples, sample_rate)
可用声音
| Voice ID | 性别 | 语言 | 风格 |
|---|---|---|---|
af_heart |
女 | 中/英 | 温暖自然 |
af_bella |
女 | 中/英 | 清晰专业 |
am_adam |
男 | 中/英 | 沉稳 |
am_michael |
男 | 中/英 | 活力 |
长文本处理
长文本自动按句分段合成，避免内存溢出：
import re
sentences = re.split(r'[。！？\.\!\?]', long_text)
all_samples = []
for s in sentences:
if s.strip():
samples, sr = kokoro.create(s.strip() + "。", voice="af_heart", lang="z")
all_samples.append(samples)
import numpy as np
combined = np.concatenate(all_samples)
sf.write("output.wav", combined, sr)
输出规范
- 生成的音频保存为 WAV 文件并返回路径
- 告知用户音频时长和文件大小
- 中英混合文本自动处理语言切换
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 · 84 lines · 26 tokens per session scan A 8c580d9c0a5b
kokoro-tts is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 569 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 2026-09-03.
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