Mineru PDF Parser Agent Skill

用 MinerU 将复杂PDF文档转换为LLM友好的Markdown/JSON格式。适用于：(1) PDF转Markdown/JSON，(2) 提取PDF中的文本、表格、公式、图像，(3) 解析学术论文、技术文档、商业报告，(4) 为RAG应用准备文档数据，(5) 批量处理PDF。触发关键词："PDF解析"、"PDF转Markdown"、"提取PDF表格/公式"、"MinerU"、"parse PDF"等。不用于：PDF的阅读/填表/签名/拆分合并（用宿主pdf工具）、Word/PPT等非PDF格式解析、只需读几页内容的场景（直接读即可，不必转换）。

6k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

658

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/staruhub/ClaudeSkills --skill mineru-pdf-parser

The instruction itself

4 sections, as written by the author

MinerU PDF Parser

将复杂PDF文档转换为机器可读的Markdown/JSON格式，适用于LLM和RAG应用。

安装

# 推荐使用uv安装
pip install uv
uv pip install -U "mineru[all]"

# 下载模型（首次使用）
mineru-models-download

快速使用

命令行

# 解析单个PDF
mineru -p input.pdf -o output_dir

# 批量解析
mineru -p pdf_folder/ -o output_dir

# 指定解析模式
mineru -p input.pdf -o output_dir --backend vlm      # VLM模式（高精度）
mineru -p input.pdf -o output_dir --backend pipeline # Pipeline模式（快速）
mineru -p input.pdf -o output_dir --backend hybrid   # 混合模式（平衡）

Python API

from mineru import MinerU

mineru = MinerU()
result = mineru.parse("document.pdf")

# 获取输出
markdown = result.to_markdown()
json_data = result.to_json()

详细API见 references/api_reference.md

解析模式选择

| 模式 | 特点 | 适用场景 |

|------|------|----------|

| pipeline | 快速、资源少 | 简单文档、纯文本PDF |

| vlm | 高精度、复杂布局 | 学术论文、公式表格文档 |

| hybrid | 平衡速度精度 | 通用场景 |

输出文件

{filename}.md - Markdown正文
{filename}_content_list.json - 结构化JSON
images/ - 提取的图像
{filename}_middle.json - 中间结果（调试）

格式详情见 references/output_formats.md

最佳实践

学术论文

mineru -p paper.pdf -o output --backend vlm

批量处理

from mineru import MinerU
import os

mineru = MinerU(backend="hybrid")
for pdf in os.listdir("pdfs/"):
    if pdf.endswith(".pdf"):
        result = mineru.parse(f"pdfs/{pdf}")
        result.save(f"output/{pdf[:-4]}/")

RAG数据准备

sections = result.get_sections()
for section in sections:
    vector_db.add(section.title, section.content)

启用GPU加速

修改 ~/.mineru.json 中 device-mode 为 cuda。

更多见 references/best_practices.md

验收标准（解析任务完成前自查）

[ ] 输出目录里 .md 与 _content_list.json 都存在,把实际路径回报用户
[ ] 抽查 1-2 页对照原 PDF:表格/公式没有明显丢失或错乱;有问题主动告知而不是静默交付
[ ] backend 选择有依据(简单文本→pipeline;公式表格密集→vlm;拿不准→hybrid)
[ ] 批量任务报告成功/失败清单,失败的给原因

已知陷阱

| 陷阱 | 具体表现 | 应对 |

|------|---------|------|

| 首次运行缺模型 | 未执行 mineru-models-download 直接解析报错 | 安装后先跑模型下载;下载体积大,提前告知用户耗时 |

| 无 GPU 硬跑 vlm | CPU 上 vlm 模式极慢,像卡死 | 无 GPU 时用 pipeline/hybrid;有 GPU 改 ~/.mineru.json 的 device-mode 为 cuda |

| 扫描件预期过高 | 低清晰度扫描 PDF 解析质量差 | 提前告知扫描件效果取决于清晰度;结果差时换 backend 重试一次,仍差则如实报告 |

| 大文件内存压力 | 数百页 PDF 单次解析内存暴涨 | 大文件分批解析或按章节拆分 |

脚本

使用 scripts/mineru_parse.py 进行解析，支持错误处理和日志记录。

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3k tokens

How to use it

Copy the folder

Take staruhub/mineru-pdf-parser from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, uv. Without those the skill loads but fails at the first command.