Aminer Pdf Ocr

Organization

AMinerOrg

aminer-pdf-ocr

[Activation] Use when the user provides a PDF and requests OCR, Markdown conversion, or structured experiment extraction. [Scope] Submit the PDF to the AMiner PDF OCR open platform (`/api/v3/paper/pdfocr/*`), poll the asynchronous job, download and unpack its ZIP, then let the Agent extract experiments from result.md using references/experiment_prompt.md. [Routing] Use pdf-citation-verifier for citation verification and aminer-academic-search / aminer-free-academic for literature search.

Overview

Publisher	AMinerOrg
Repository	`aminer-open-skill`
Skill name	`aminer-pdf-ocr`
Stars	66
Forks	19
Bundled files	10
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
10 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by AMinerOrg on GitHub. Read the source before you install it.

Installation

Install the Aminer Pdf Ocr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/AMinerOrg/aminer-open-skill/tree/main/skills/aminer-pdf-ocr
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/AMinerOrg/aminer-open-skill.git /tmp/aminer-open-skill
mkdir -p .claude/skills
cp -r /tmp/aminer-open-skill/skills/aminer-pdf-ocr .claude/skills/aminer-pdf-ocr

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aminer Pdf Ocr in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aminer Pdf Ocr on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aminer Pdf Ocr is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PDF OCR + Experiment Extraction

The Python wrapper validates a PDF, uploads it to the AMiner PDF OCR open platform, handles queue backoff, polls the asynchronous job, downloads the temporary result ZIP, and writes compatible local artifacts. The Agent then reads result.md and follows references/experiment_prompt.md to create experiments.json.

Pre-flight

Confirm AMINER_API_KEY exists (same token as other AMiner skills). If missing, stop and send the user to https://open.aminer.cn/open/board?tab=control. Never print its value. OPEN_PLATFORM_TOKEN is accepted only as a deprecated fallback.
Install requests and pypdf from requirements.txt.
Confirm the input is a local PDF or an HTTP(S) URL. The open platform accepts only unencrypted PDFs of 1-30 pages and at most 10 MiB. Refuse localhost / private-network URLs.

Run

bash
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/ocr.py" --input "/abs/path/to/paper.pdf"

Options include --output-dir, --request-timeout, --poll-timeout, --max-upload-attempts, --no-save-images, and --output. The old local parser, backend, page-range, formula, and table options are not supported.

API contract

Endpoints: POST /api/v3/paper/pdfocr/upload and GET /api/v3/paper/pdfocr/result on https://datacenter.aminer.cn/gateway/open_platform.
Upload and polling use the same token (AMINER_API_KEY) and send Authorization, X-Platform (current host: claude-code / cursor / codex / openclaw; unknown if it cannot be determined), X-Skill-Name: aminer-pdf-ocr, and X-Skill-Version (this file's frontmatter version).
Upload code: 202 means queued, not completed. A reused upload may return code: 200; always use its returned job_id.
Do not use success, HTTP status, or code alone to decide success. Inspect data.status and data.is_finish.
preparing, queued, and running are polled. success downloads the ZIP. failed, timeout, queue_timeout, expired, and unknown stop.
data.queue_full is retried with bounded backoff using retry_after_seconds.
The temporary download URL is fetched directly without Authorization and is not saved in response.json.
ZIP entries are discovered by .md and _middle.json suffixes; document/ is not a protocol.

Experiment extraction

Unless OCR-only is explicitly requested, read the complete result.md, follow references/experiment_prompt.md, write one JSON object to experiments.json, and show the same full JSON in the response. Do not add justification fields or invent unsupported experiments, datasets, metrics, or scores. If OCR fails, report the error and do not fabricate extraction output.

Real example

The default local sample is data/pdf/applsci-14-11736.pdf (untracked; place it yourself). The live test is opt-in: set RUN_PDFOCR_LIVE=1 together with AMINER_API_KEY. It is skipped by default and never runs without both the credential and fixture.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aminer Pdf Ocr AI skill do?

Why use Aminer Pdf Ocr on TypingMind?

Because you install it once and use it with any model. Aminer Pdf Ocr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aminer Pdf Ocr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AMinerOrg/aminer-open-skill/tree/main/skills/aminer-pdf-ocr. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aminer Pdf Ocr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aminer Pdf Ocr?

As many as you like. As long as a model supports skills, you can use Aminer Pdf Ocr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aminer Pdf Ocr AI skill free?

Yes. It is published on GitHub by AMinerOrg under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

PDF OCR + Experiment Extraction

Pre-flight

Run

API contract

Experiment extraction

Real example

Bundled files

Frequently asked questions

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