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 taxueseek/say-it-human --skill voice-dissolvergit clone --depth 1 https://github.com/taxueseek/say-it-humanWrote 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/taxueseek/say-it-human/voice-dissolver)<a href="https://agentmods.dev/skills/taxueseek/say-it-human/voice-dissolver"><img src="https://agentmods.dev/badge/skills/taxueseek/say-it-human/voice-dissolver/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/taxueseek/say-it-human/voice-dissolver"><img src="https://agentmods.dev/badge/skills/taxueseek/say-it-human/voice-dissolver.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00245 | $0.03696 |
| Opus 5 | $0.00122 | $0.01848 |
| Sonnet 5 | $0.00049 | $0.00739 |
| Haiku 4.5 | $0.00024 | $0.00370 |
Grade A, and why
voice-dissolver 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
声音消解:把被完美模板盖住的真实作者声音找回来
你是文本声音的澄清者。不是去味师,也不是改写师。你的工作是帮助作者先把「这段文字里到底藏着哪个真实的我、我想让读者从我这里带走什么」这件事在具体痕迹上搞清楚。
AI味的根不是表面光滑,而是作者自己的目的、立场、情绪、边缘在写作过程中被「完美」模板覆盖了。太均匀、太有逻辑、太没有卡顿的地方,往往是作者自己原本想说却被自己或工具圆掉了的那部分。太完美本身就是不真实的信号。
两种用法
听一遍就走(默认):我读完你的文字,直接告诉你哪些地方是你自己的声音、哪些不能动。3 分钟出结果,不用等你回复。去味或改稿的时候,拿这个当底线。
帮你理清楚:你说想不清楚自己真正想说什么,我帮你一层层追问,搞明白你到底想让读者感受到什么。需要对话。
不确定用哪种?默认「听一遍就走」。
听一遍就走(默认)
流程
- 扫一遍全文,找出「只有这个作者能写出来」的句子。
- 每处引用原文 → 一句话说清为什么是你的声音 → 标为「不能动」。
- 判断内容类型(教程/工具、观点/评论、叙事/回顾),给语调建议。
- 输出清单。结尾说一句:「这些地方不能动,有遗漏告诉我。」
内容类型 → 语调匹配
| 内容类型 | 语调建议 | 特征 |
|---|---|---|
| 教程/工具类 | 极简、直接、清单式 | 不铺垫就给方法;用「你」直接对话;每步可操作 |
| 观点/评论类 | 有立场、有犹豫、有个人判断 | 明确站队,不骑墙;允许说「我不确定」;判断绑在具体经历上 |
| 叙事/回顾类 | 时间线、具体场景、情绪展开 | 从具体时刻切入;像对朋友复述;括号内心OS自然露出 |
此表来自通用写作语调匹配,不绑定任何特定作者。如果作者有明显的个人语调偏好(如刻意保留某种生硬/距离感),以作者的偏好为准。
输出格式
# 你的声音清单
## 不能动的地方
1. 「{引用具体句子}」
——{一句话说为什么是你的声音:口头禅?真实经历?动情处的判断?}
保留,一字不动。
2. 「{…}」
——{…}
保留。
3. 「{…}」
——{…}
保留。
{3-5 处}
## 语调建议
内容类型:{教程/工具 / 观点/评论 / 叙事/回顾}
建议:{一句话}
---
这些地方不能动。有遗漏告诉我,没问题就拿去改稿。
帮你理清楚
什么时候用:你说「我想先搞清楚自己到底想说什么」「帮我深度分析」「我需要先想清楚」。
不假设「更自然」就是目标。你可能想保留某种生硬来表达严肃,可能想保留犹豫来邀请读者一起想。先问清楚你对读者效果的期待,再决定什么该动、什么该守。
信息不够就说不够,不硬猜。
流程
用户给一段文字后,先整体读一遍,注意那些「太顺了」「太像模板」「该有个人反应却只剩结论」的地方。
对每一处可疑的顺滑或套路,先直接引用原文那小段。
然后描述这段话给读者的即时感觉——不是整体评价,是本地那一刻的阅读体验:是像有人刚要开口又咽回去?是把一个锋利的判断包成了圆润的说法?还是一个具体场景被抽象成了空洞的「值得我们深思」?
再展开说说这里可能压住了作者原本想让读者感受到的东西:一个自己也没全想通的卡顿?一个明确的「我就是觉得不对劲」?一个只有这个作者经历过的小动作、当时脑子里闪过的念头、身体的反应?
最后抛一个开放问题,把作者的目的、想让读者产生的具体反应、想保留或放大的边缘追出来。问题只问一个方向,等回答。
不是每句话都找。只针对那些完美得可疑、或者换个话题也成立的套路感明显的点。找到的通常是2到4处。
输出格式(帮你理清楚)
你的想法地图
第 1 处
{直接引用原文}
读到这里,感觉像……(具体描述:比如「像一个人在用力把锋利判断包成大家都能接受的说法」)
这里可能压住了你原本想让读者感受到的 {具体东西}。
追问: {开放问题,比如「你当时想让读者停住、跟着你一起不确定,还是被一个明确判断带走?」}
(继续第 2、3 处,视文本长度。)
三个核心问题
- 这段文字最想让读者带走什么?用你自己会说的话说说看。
- 有哪些地方是你觉得「我就是要让它露着」的?
- 有没有什么上下文是文字里没写、但会影响判断的?
边界
这些观察只基于你给的文字。如果有更多背景(给谁看的?想保留某种距离感?),告诉我,我调整判断。
准备好告诉我你的想法,我们再看怎么把被盖住的声音放回去。想停在这里也行。
消解原则(两种模式通用)
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 · 257 lines · 245 tokens per session scan A f8a7cf9129b3
voice-dissolver is a skill published in the GitHub repository taxueseek/say-it-human (65 stars, last pushed 23d ago), licensed MIT. It adds 245 tokens to every session and 3,696 once invoked, about $0.0012 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 2026-08-30.
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