speak-zhouli

speak-zhouli is a skill for Codex from Aspirin0000/zhouli-translator. It costs 104 tokens per session (4,455 once invoked), scanned A, original, MIT.

A writing guide that changes modern Chinese into a formal, deliberately old-fashioned style inspired by the rites of the Zhou dynasty, or explains that style in ordinary language.

In plain words
What is it for?
Use it to rewrite messages as polite but humorous ceremonial speech, settle arguments in that style, praise or comment on public topics, or translate Zhou-style wording back into clear Chinese.
Why use it?
It lets users keep the original meaning and speaker while changing the tone, including when expressing criticism or anger without repeating explicit insults.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to rewrite messages as polite but humorous ceremonial speech, settle arguments in that style, praise or comment on public topics, or translate Zhou-style wording back into clear Chinese.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aspirin0000/zhouli-translator/speak-zhouli
Install

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.

Any agent
npx skills add Aspirin0000/zhouli-translator --skill speak-zhouli
Clone the repo
git clone --depth 1 https://github.com/Aspirin0000/zhouli-translator

Made for: Codex.

Wrote 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.

agentmods badge for speak-zhouli

README.md
[![agentmods](https://agentmods.dev/badge/skills/aspirin0000/zhouli-translator/speak-zhouli/github.svg)](https://agentmods.dev/skills/aspirin0000/zhouli-translator/speak-zhouli)
Your own site
<a href="https://agentmods.dev/skills/aspirin0000/zhouli-translator/speak-zhouli"><img src="https://agentmods.dev/badge/skills/aspirin0000/zhouli-translator/speak-zhouli/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.

agentmods 80×15 button for speak-zhouli

Your own site · 80×15
<a href="https://agentmods.dev/skills/aspirin0000/zhouli-translator/speak-zhouli"><img src="https://agentmods.dev/badge/skills/aspirin0000/zhouli-translator/speak-zhouli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,455 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00104 $0.04455
Opus 5 $0.00052 $0.02227
Sonnet 5 $0.00021 $0.00891
Haiku 4.5 $0.00010 $0.00445

Measured 13d ago against content hash 854ac475defd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

speak-zhouli 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 13d 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.

public/downloads/speak-zhouli-SKILL.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

合乎周礼

把用户的话改写成人人能看懂、一本正经而略显荒唐的“周礼白话翻译腔”,也能把这类周礼体翻回清楚直接的人话。让笑点来自严密论证与意外结论,不来自晦涩古文;让释礼来自准确还原,不来自继续整活。

工作步骤

  1. 先判断用户要“问礼”还是“释礼”。用户要求合乎周礼、周礼体、改写、圆场、辩经、痛陈时,进入问礼;用户要求释礼、翻回人话、解释这段周礼体、反向翻译、看懂这段话时,进入释礼。
  2. 先辨认原话的事实、立场、对象与情绪,不擅自改变用户本意。
  3. 先判定发言主体:若原话包含“我、我们、我的、我该、我如何、怎么回复、怎么说”等信号,或原话本身以“我”开头,默认替说话者本人写一段可以直接发出去的话,用第一人称“我/我们”;不要改成“你/您/他”的旁观评价。
  4. 若原话是在评价影视梗、公共事件、第三方人物或他人行为,例如“华强买瓜怎么说”“NiKo夺冠怎么夸”,则可以使用第三视角评议。
  5. 严守代词和动作归属:原话说“我做了网站”,输出仍应是“我做了/我造了/我建了”,不能写成“你建了这网站”;原话说“观众感谢我”,输出仍应是“观众/大家感谢我”,不能写成“他们感谢你”;原话说“你三连我的视频”,这里的“你”是对方,不是发言者。
  6. 若原话是“我对你/你的……表达不满、辱骂、威胁或攻击”,必须保持“我=发言者,您/你/阁下=被指向对象”。不能推断对方说了什么或做了什么;如果原话没有交代原因,只能写“此事/眼前这番争执/这般局面/阁下与我之间的分寸”。不能写成“你出言粗鄙、阁下说出这般粗鄙之语、你骂了我、你伤了我、你以禽兽之名相辱、阁下这番话”,除非原话明确说“你骂我/别人骂我/他说我”。
  7. 遇到粗口、辱骂、爆粗、想骂人、想喷人、强烈情绪句时,任务不是劝发言者冷静,而是把同一份不满、斥责或吐槽换成合乎周礼的表达。不要写“你说出这句话/今天你……/你这句话……/你的事……”,也不要把主体写成“我不愿失礼,所以我先忍住”。若原话只有怒气、没有对象,必须补一个外部对象或外部缘由,如“此事/此人/眼前这般行径/阁下此举”,不能把过错写回发言者自身。若原话是“我/我要/我想/我会……你/你的亲友……”这类指向对方的粗口或威胁,必须保留“我在表达怒意、你是被指向对象”的关系,但不能输出伤害、性羞辱或威胁;要降级成“阁下此举令我不平/此事越过分寸/我今日有怒但只论礼数”的体面斥责。禁止写成三省吾身式自省,不要出现“先问自己/我可曾/开口的人自己失礼/失礼的是我”这类把矛头转回发言者的话。可以保留怒气和锋芒,但严禁复述露骨侮辱词;即使原话是在转述别人骂了什么,也要改写成“粗鄙之语、污言秽语、禽兽之名、无礼之言”,不要原样写出脏词,也不要攻击具体群体。
  8. 若原话是引用或评价危险话,例如“他说……这句话怎么评价”,不要当成用户本人要实施,也不要复述威胁词。应评价为“此言越界、以伤害压过道理、乱了分寸”,保留评论功能而不传播原危险表达。
  9. 遇到“渗透测试、安全巡检、漏洞检查”这类网络安全话题,不要一上来批评用户。若语境像授权测试,应改写成“受托巡检门户、查门闩、报修补”的合礼表达;若明确是黑进、盗号、绕过登录、偷数据、留后门,则温和拒绝,不提供步骤。
  10. 按用户要求选择辞气;没有指定时,根据语境选最自然的一种。
  11. 先讲一个能听懂的故事、常识、自然现象或古代旧事,再转到眼前小事。
  12. 像课本白话译文那样,把省略的主语、关系和名分补出来:谁对谁、该尽什么本分、乱了什么分寸。
  13. 使用“承认—转折—类比—定论或反问”的结构,把小事郑重地说圆。
  14. 写完后删去生僻文言、重复说理、空泛赞美和机械套话。
  15. 默认只输出改写或释义结果;用户要求分析时再解释写法。

释礼

当用户要求“释礼”“翻回人话”“解释这段周礼体”“反向翻译”“这段话什么意思”时,进入释礼模式。

  • 任务是把周礼体翻回人话,不要继续写周礼体,不要再新编古人故事。
  • 直接输出原文意思,第一句就进入释义;不要以“这段话的意思是”开头,也不要以“人话说就是”“翻译一下”“说白了”“本质上是”开头。
  • 原文是第一人称,就继续用“我/我们”还原;不要改成“他其实”“作者其实”。
  • 保留原文的对象、立场、语气和社交关系。谁在评价谁、谁想回复谁、谁担心什么,都要说清。
  • 若原文是在求一句体面说法,只解释“我在求一个体面/委婉的说法”这个动作,不要继续代写最终回复。
  • 若原文是在拉票、求赞、求投币、解释限流、回应评论或拒绝危险请求,要直接翻出这个意图,但不要新增原文没有的事实。
  • 可以按用户要求选择释法:直白释义、耐心讲明、潜台词版、锐评拆穿。锐评只能拆原文已有话术,不要新增罪名。
  • 输出短、准、自然,像网友看懂后顺手解释;不加标题、编号、项目符号或 Markdown。

Read the full file on GitHub · 148 lines

Files

What ships with it

1 file beside speak-zhouli-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.

Changes

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.

  1. 13d ago First seen · 148 lines · 104 tokens per session scan A 854ac475defd

Subscribe to this mod's changes

speak-zhouli is a skill published in the GitHub repository Aspirin0000/zhouli-translator (313 stars, last pushed today), licensed MIT. It adds 104 tokens to every session and 4,455 once invoked, about $0.0005 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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