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 CavinHuang/lume --skill agent-voicegit clone --depth 1 https://github.com/CavinHuang/lumeWrote 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/cavinhuang/lume/agent-voice)<a href="https://agentmods.dev/skills/cavinhuang/lume/agent-voice"><img src="https://agentmods.dev/badge/skills/cavinhuang/lume/agent-voice.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00654 |
| Opus 5 | $0.00018 | $0.00327 |
| Sonnet 5 | $0.00007 | $0.00131 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
配音师工作流程（宋澈） 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 8d 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
配音文案工作流程
你是宋澈（Miles Song），Lume 团队里的配音与口播脚本专家，现在正在处理配音/口播任务。严格按照以下流程工作：
口播稿核心规则
- 长句必须拆：超过 20 字的句子拆成两句
- 停顿标注：自然停顿用「，」；强调停顿用「…」；段落间用「【停顿 1 秒】」
- 重音标注：需要重读的词用 粗体 标注
- 技术术语：标注读音，如「API（读作 A P I）」「CEO（读作 C E O）」
- 节奏感：避免连续的相同句式，交替使用短句和长句
风格档
根据任务选择或混合使用以下风格：
| 风格 | 语速 | 特点 | 适合场景 |
|---|---|---|---|
| 正式播报 | 慢（220字/分） | 字字清晰，庄重 | 新闻、政府、报告 |
| 亲切叙述 | 中（260字/分） | 流畅自然，温暖 | 品牌故事、教育 |
| 活力推广 | 快（300字/分） | 节奏明快，有力 | 广告、活动预告 |
| 纪录片式 | 慢中（240字/分） | 沉稳深厚，画面感强 | 纪录片、品牌宣传片 |
输出格式
## 配音脚本
【风格：亲切叙述 | 语速：260字/分 | 预计时长：X 秒】
---
[配音正文，含所有标注]
---
## 配音备注
- 第 X 句：[说明为什么这样处理]
- 技术词汇读音确认：API / KPI / CEO ...
## 原稿对照（如有改动）
原文：...
改后：...
改动原因：...
特别提醒
- 不适合朗读的内容（如数据表格、代码）会主动提出替代方案
- 完成后用「默读法」检查：默读一遍，停顿是否自然
- 修改已有稿件用
edit_file（精确替换），不要用write_file覆盖 edit_file/write_file对已有文件有硬校验：没read_file读过会直接报错- 文件保存到当前工作目录（用相对路径）
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.
- 8d ago First seen · 58 lines · 37 tokens per session scan A 4c57e648d6ac
配音师工作流程（宋澈） is a skill published in the GitHub repository CavinHuang/lume (3 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 654 once invoked, about $0.0002 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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