Borrowing it
Nothing to install: this file belongs to ThreeFish-AI/negentropy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ThreeFish-AI/negentropy/master/.agent/skills/doc-translator/SKILL.mdgit clone --depth 1 https://github.com/ThreeFish-AI/negentropyWrote 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/threefish-ai/negentropy/doc-translator)<a href="https://agentmods.dev/skills/threefish-ai/negentropy/doc-translator"><img src="https://agentmods.dev/badge/skills/threefish-ai/negentropy/doc-translator.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.02244 |
| Opus 5 | $0.00017 | $0.01122 |
| Sonnet 5 | $0.00007 | $0.00449 |
| Haiku 4.5 | $0.00003 | $0.00224 |
Grade A, and why
doc-translator 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 7d 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 — 333 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document Translator (Coordinator)
按照下文 Workflow，协调各个子技能完成文档的完整翻译流程，包括内容提取、中文翻译、格式化和最终文档生成。
协调职责
1. 流程编排
- 分析文档类型和大小，选择合适的处理策略
- 协调各子技能的执行顺序
- 管理数据在各技能间的流转
- 处理批次管理和进度跟踪
2. 资源管理
- 创建和管理输出目录结构
- 协调图片资源的存储和引用
- 管理临时文件的创建和清理
- 维护工作环境的整洁
3. 质量控制
- 监控各步骤的执行状态
- 验证每个阶段的输出质量
- 处理错误和异常情况
- 生成详细的处理报告
核心工作流程
1. 初始化阶段
输入: 源文档路径或 URL
分析:
- 文档类型（PDF/Web）
- 文档大小（页数/字数）
- 处理复杂度评估
- 选择处理策略
2. 准备工作
创建目录结构:
/path/to/source/
├── translate/ # 翻译输出目录
│ ├── {doc_name}.md # 最终翻译文档
│ └── images/ # 图片资源
│ └── {doc_name}/ # 文档相关图片
└── temp/ # 临时文件目录
├── batch_*.md # 批次处理文件
└── progress.json # 进度跟踪文件
3. 批次处理策略
批次大小限制:
- 最大页数: 30 页/批次
- 最大段落数: 60 段落/批次
- 最大字数: 6000 字/批次
批次划分:
- 优先级: 页数 > 段落数 > 字数
- 在章节、段落等自然边界处分割
- 确保每个批次的内容相对完整
4. 处理流程
小文档直接处理
doc-translator (协调器)
├── 1. pdf-reader 或 web-translator (内容提取)
│ └── 输出: 原始 Markdown 内容
├── 2. zh-translator (中文翻译)
│ └── 输出: 中文 Markdown 内容
├── 3. markdown-formatter (格式优化)
│ └── 输出: 格式化的中文 Markdown
├── 4. 质量检查和修复
└── 5. 生成最终文档
大文档批次处理
doc-translator (协调器)
├── batch-processor (批次管理)
│ ├── 1. 创建批次计划
│ └── 2. 循环处理每个批次:
│ ├── pdf-reader/web-translator (提取)
│ ├── zh-translator (翻译)
│ ├── markdown-formatter (格式化)
│ ├── 质量检查
│ └── 追加到目标文档
├── 3. 合并所有批次结果
├── 4. 整体格式优化
└── 5. 生成最终文档和报告
详细执行步骤
步骤 1: 批次规划
- 根据源文档内容制定批次处理计划
- 创建目标 Markdown 文档
- 初始化进度跟踪
步骤 2: 批次处理循环
FOR EACH batch:
1. 检查是否所有批次处理完成
2. 创建批次 Markdown 文档
3. 内容提取:
- PDF: pdf-reader
- Web: web-translator
4. 内容翻译:
- zh-translator
5. 格式化:
- markdown-formatter
6. 质量检查:
- 图片引用验证
- 格式一致性检查
- 翻译准确性检查
7. 追加到目标文档
8. 清理批次临时文件
END FOR
步骤 3: 最终处理
- 检查整体转换与翻译的正确性
- 修复发现的问题
- 优化文档整体布局
- 生成处理报告
子技能调用接口
pdf-reader 调用
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.
- 7d ago First seen · 333 lines · 34 tokens per session scan A 5d87a58a2274
doc-translator is a skill published in the GitHub repository ThreeFish-AI/negentropy (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 34 tokens to every session and 2,244 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.
Other skills, from other repositories
literature
Load when extracting GEO accessions, dataset metadata, and downloadable references from a scientific paper (PDF / URL / DOI / PubMed ID / raw text) for downstream omics analysis. Skip when the dataset is already in hand; only routing a query (use orchestrator).
pdf_translator
Extract text from PDF files, translate it to a target language, and save the result as a Markdown file. Use this skill when the user wants to translate a PDF document or asks to "convert PDF to Chinese".
translate-book
Translate books (PDF/DOCX/EPUB) into any language using parallel sub-agents. Converts input -> Markdown chunks -> translated chunks -> HTML/DOCX/EPUB/PDF.
wechat-article-ingest
A tool that converts public WeChat Official Account articles, or PDF copies of them, into Markdown notes. It can also extract the article's main viewpoints and create linked questions for further thinking.
pdf-fill
Fill PDF form fields from a data dict.
paper-writing
Write and typeset formal documents — academic papers, reports, articles — using Markdown + Pandoc and LaTeX. Convert between formats (md↔pdf↔docx↔tex), manage citations with BibTeX/CSL. Keyless, local. Use when asked to "write a paper", "format this as LaTeX", "convert to PDF/Word", "add citations".