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 liyecom/liye-ai --skill pdfgit clone --depth 1 https://github.com/liyecom/liye-aiWrote 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/liyecom/liye-ai/pdf)<a href="https://agentmods.dev/skills/liyecom/liye-ai/pdf"><img src="https://agentmods.dev/badge/skills/liyecom/liye-ai/pdf.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 | $0.00019 | $0.00896 |
| Opus 5 | $0.00010 | $0.00448 |
| Sonnet 5 | $0.00004 | $0.00179 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade A, and why
pdf 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
来源: ComposioHQ/awesome-claude-skills 适配: LiYe OS 三层架构
综合 PDF 操作工具，支持提取文本/表格/元数据，合并/拆分文档，添加注释，处理表单。
When to Use This Skill
当 Claude 需要处理 PDF 文件时：
- 从 PDF 中提取文本、表格或元数据
- 创建新的 PDF 文档
- 合并或拆分 PDF 文件
- 添加注释或批注
- 处理 PDF 表单
Core Capabilities
1. 文本提取
- 提取全文内容
- 保留文档结构
- 识别标题和段落层级
- OCR 支持（扫描件）
2. 表格提取
- 识别表格结构
- 导出为结构化数据
- 支持复杂嵌套表格
3. 元数据处理
- 读取文档属性
- 提取作者、创建日期等信息
- 修改文档元数据
4. 文档操作
- 合并多个 PDF
- 拆分为多个文件
- 页面重排序
- 提取特定页面
5. 注释与表单
- 添加高亮和批注
- 填写表单字段
- 创建可填写表单
Usage Examples
示例 1: 提取研究论文内容
用户: 提取这篇医学论文的摘要和结论
Claude: [使用 pdf 技能提取指定章节内容]
示例 2: 合并多个报告
用户: 把这些季度报告合并成一个年度汇总
Claude: [使用 pdf 技能合并文件，添加目录页]
示例 3: 提取表格数据
用户: 从这个 PDF 报告中提取数据表格
Claude: [使用 pdf 技能识别并提取表格，转为结构化格式]
Dependencies
- Python: PyPDF2, pdfplumber, reportlab, PyMuPDF
- 或 Node.js: pdf-lib, pdf-parse
LiYe OS Integration
业务域引用
此技能被以下业务域引用：
- 05_Medical_Intelligence: 医学文献、临床指南解析
- 01_Research_Intelligence: 学术论文分析
- 04_Business_Operations: 商务文档处理
三层架构位置
- 物理层 (本文件): Skills/00_Core_Utilities/document-processing/pdf/
- 逻辑层索引: Skills/{domain}/index.yaml
- L3 指令层: .claude/skills/{domain}/pdf/
Created: 2025-12-28 | Adapted for LiYe OS
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 · 120 lines · 19 tokens per session scan A 7049283b8f18
pdf is a skill published in the GitHub repository liyecom/liye-ai (33 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 896 once invoked, about $0.0001 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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