Who it is forA Claude Code or Codex user asking questions about a 300 page contract or book.
The problemDumping a whole long document into context overflows it, and answers come without page references.
The outcomeAn agent that reads progressively, follows continuation locators and cites the page and block it used.
What you need first
- Python 3.11 to 3.14 in a virtual environment
- Windows, Linux or macOS; CPU works, compatible GPUs are used automatically
- Model downloads for the tier you choose
- Optional: Node.js for npx to install the agent skill
Steps
- Send your agent the README's install message, which starts with
npx skills add opendatalab/MinerU --skill mineru --global --yes - Ask it to read a file; it starts with
mineru parse document.pdf --json, which covers the first 10 PDF pages - Let it continue with the returned locators instead of re-parsing the whole file
- Ask it to keep the doc, tier, page and block locators in its answers so every claim is traceable
- Expect it to ask before using remote parsing, adding watches or changing persistent config, as the Agent Contract requires
Prompt for your agent
Install the opendatalab/MinerU skill, then read <document> progressively with mineru parse and the returned locators. Answer <question> and cite the page and block locator for every claim.
Caveat. The skill install message also asks the agent to record a global preference for MinerU, so read it before sending if you do not want that.
Use this in your AI agent
Ask your agent
Using the Deduped MCP, get the setup steps for opendatalab/MinerU and "Let your agent read long documents page by page"
Add Deduped to Claude Code once
claude mcp add --transport http deduped https://dedupedai.com/mcp
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