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 nickolaslin33/agent-skills --skill clear-technical-chinesegit clone --depth 1 https://github.com/nickolaslin33/agent-skillsWrote 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/nickolaslin33/agent-skills/clear-technical-chinese)<a href="https://agentmods.dev/skills/nickolaslin33/agent-skills/clear-technical-chinese"><img src="https://agentmods.dev/badge/skills/nickolaslin33/agent-skills/clear-technical-chinese/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/nickolaslin33/agent-skills/clear-technical-chinese"><img src="https://agentmods.dev/badge/skills/nickolaslin33/agent-skills/clear-technical-chinese.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 | $0.00405 | $0.05659 |
| Opus 5.5 | $0.00162 | $0.02264 |
| Sonnet 5.5 | $0.00081 | $0.01132 |
| Haiku 4.5 | $0.00040 | $0.00566 |
Grade A, and why
clear-technical-chinese 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 1mo 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clear Technical Chinese — 清晰中文技術寫作
目標
首要目標不是讓文字顯得專業、聰明、有力或有文采，而是：
讓讀者第一次閱讀就能理解，不需要猜測、自行補完省略的推論，或反覆重讀。
判斷一句話好不好，標準只有一個：讀者看完知不知道你具體在說什麼。一句話「看起來很有力」但讓讀者必須停下來解讀，就是失敗的。清楚比有力重要。
先選模式
兩種模式共用下面的共通規則，差別在資訊密度與完整度。
| 情境 | 模式 |
|---|---|
| 撰寫、修改、潤飾 README / SKILL.md / 規格 / 設計文件 / 技術說明 / 操作流程 / API 說明 | 技術文件模式 |
| 一般問答、進度回報、說明剛才做了什麼、討論方案、回答「這是什麼」 | 日常回覆模式 |
不確定時，看讀者手上有沒有脈絡：
- 文件是寫給未來、不在場、沒看過這段對話的人看的 → 要完整。
- 回覆是寫給眼前正在對話的人看的，他已經知道背景 → 要短。
一次回覆裡同時包含兩者時分開處理。 例如使用者要你寫一份 README：README 的內容本身用技術文件模式，而你在對話裡說明「我改了哪幾段、為什麼」的那段話，用日常回覆模式。不要因為在寫文件，就把整個回覆都寫成文件的口氣。
共通規則
1. 自然的繁體中文
用台灣軟體工作者實際會講的說法。如果一句話只有工程師看得懂，但一般熟悉軟體工作的人不會自然這樣說，就換成更清楚的說法。
2. 不要英文直譯
英文句型直接搬過來會產生「看得懂但很卡」的中文。常見的幾種：
| 直譯 | 自然的說法 |
|---|---|
| 這個功能是被設計來處理 X 的 | 這個功能用來處理 X |
| 基於這個原因，我們決定… | 所以我們決定… |
| 它提供了一個方式讓你可以… | 你可以用它來… |
| 在大多數的情況下 | 多數情況 |
| 確保你已經安裝了 Node | 先確認 Node 已安裝 |
| 一個好的做法是先跑測試 | 建議先跑測試 |
| 這將會導致資料遺失 | 這會造成資料遺失 |
| 不要猶豫去問我 | 有問題直接問 |
判斷方式：把句子唸出來。如果唸起來像翻譯小說而不像同事講話，就改寫。
3. 不要工程師黑話
黑話的問題不是不專業，是它把具體發生的事情藏起來了。「炸掉」可能是 exception、可能是回傳錯誤值、可能是整個程序退出——讀者無從判斷。
| 別寫 | 改成 |
|---|---|
| 沒破 | 確認既有功能是否正常 |
| 炸掉 | 發生錯誤 |
| 卡死 | 阻礙後續流程 |
| 掉東西 | 資訊遺失 |
| 撈不到 | 無法取得 |
| 擋路 | 影響後續工作 |
| 有兩個坑 | 有兩個需要注意的問題 |
| 寄生在流程裡 | 整合到既有流程 |
| 程式碼欠的 | 程式碼或系統尚未處理的技術問題 |
完整對照表在 references/writing-guide.md。
4. 技術詞不強制翻譯
如果英文術語在軟體工程中更常見、更精準，或翻成中文反而產生歧義，直接保留英文。以下這類通常保留原文：
schema、diff、commit、commit SHA、repo、runtime、payload、endpoint、handler、session、subagent、CLI、API、frontmatter
判斷原則：哪一種說法能讓讀者最快知道具體指的是什麼，就用哪一種。 不是中文越多越好。
contract 特別要小心。 不要一律翻成「契約」或「合約」——要先看上下文是哪一種，然後盡量寫出實際規則：
- 不要寫「驗證分層契約」
- 改寫「新增測試，確認 service layer 只能透過指定介面存取資料」
依情境可用：API contract → API 輸入輸出規格；interface contract → 介面規格；data contract → 資料格式與欄位規範；behavioral contract → 行為規則。如果沒有自然且精準的中文詞，直接保留 contract，並在第一次出現時說明它具體代表什麼。
5. 不要過度壓縮因果
不要為了簡短或有力，把完整的因果關係壓成口號。
- ❌ 代號是指標，不是線索。
- ✅ 代號只能指向某個內容，本身不足以幫助使用者重新建立工作脈絡。
- ❌ 問題不是忘記，是從來沒進去過。
- ✅ 表面上看起來像是後來忘記，但實際上有些內容在當時就沒有形成足夠的理解。
What ships with it
2 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.
- 1mo ago First seen · 274 lines · 405 tokens per session scan A 8e720a991e08
clear-technical-chinese is a skill published in the GitHub repository nickolaslin33/agent-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 405 tokens to every session and 5,659 once invoked, about $0.0016 per session on Opus 5.5. 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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