Extract academic paper metadata
Skill iterationlayer/skills/skills/extract-academic-paper-metadata
Extract title, authors, abstract, and citation info from academic papers.From its SKILL.md
npx -y skills add iterationlayer/skills --skill extract-academic-paper-metadataAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
11.7 KB, as published. Nobody here has run it
Extract Academic Paper Metadata
Research teams and academic platforms use this recipe to extract metadata from a paper. Upload a PDF paper and receive structured JSON with title, authors, abstract, publication date, and keywords — ready for indexing, citation analysis, or a literature review tool.
APIs Used
Document Extraction (1 credit per page)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
curl -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "paper.pdf",
"url": "https://example.com/papers/research-paper.pdf"
}
],
"schema": {
"fields": [
{
"name": "title",
"type": "TEXT",
"description": "Title of the academic paper"
},
{
"name": "authors",
"type": "ARRAY",
"description": "List of paper authors",
"fields": [
{
"name": "name",
"type": "TEXT",
"description": "Full name of the author"
}
]
},
{
"name": "abstract",
"type": "TEXTAREA",
"description": "Paper abstract"
},
{
"name": "published_date",
"type": "DATE",
"description": "Publication date of the paper"
},
{
"name": "keywords",
"type": "ARRAY",
"description": "Subject keywords or tags",
"fields": [
{
"name": "keyword",
"type": "TEXT",
"description": "A keyword or topic tag"
}
]
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.extractDocument({
files: [
{
type: "url",
name: "paper.pdf",
url: "https://example.com/papers/research-paper.pdf",
},
],
schema: {
fields: [
{
name: "title",
type: "TEXT",
description: "Title of the academic paper",
},
{
name: "authors",
type: "ARRAY",
description: "List of paper authors",
fields: [
{
name: "name",
type: "TEXT",
description: "Full name of the author",
},
],
},
{
name: "abstract",
type: "TEXTAREA",
description: "Paper abstract",
},
{
name: "published_date",
type: "DATE",
description: "Publication date of the paper",
},
{
name: "keywords",
type: "ARRAY",
description: "Subject keywords or tags",
fields: [
{
name: "keyword",
type: "TEXT",
description: "A keyword or topic tag",
},
],
},
],
},
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.extract_document(
files=[
{
"type": "url",
"name": "paper.pdf",
"url": "https://example.com/papers/research-paper.pdf",
}
],
schema={
"fields": [
{
"name": "title",
"type": "TEXT",
"description": "Title of the academic paper",
},
{
"name": "authors",
"type": "ARRAY",
"description": "List of paper authors",
"fields": [
{
"name": "name",
"type": "TEXT",
"description": "Full name of the author",
},
],
},
{
"name": "abstract",
"type": "TEXTAREA",
"description": "Paper abstract",
},
{
"name": "published_date",
"type": "DATE",
"description": "Publication date of the paper",
},
{
"name": "keywords",
"type": "ARRAY",
"description": "Subject keywords or tags",
"fields": [
{
"name": "keyword",
"type": "TEXT",
"description": "A keyword or topic tag",
},
],
},
]
},
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.ExtractDocument(il.ExtractDocumentRequest{
Files: []il.FileInput{
il.FileInput{
Type: "url",
Name: "paper.pdf",
Url: "https://example.com/papers/research-paper.pdf",
},
},
Schema: il.ExtractionSchema{
Fields: []any{
il.TextFieldConfig{
Name: "title",
Type: "TEXT",
Description: "Title of the academic paper",
},
il.ArrayFieldConfig{
Name: "authors",
Type: "ARRAY",
Description: "List of paper authors",
Fields: []any{
il.TextFieldConfig{
Name: "name",
Type: "TEXT",
Description: "Full name of the author",
},
},
},
il.TextareaFieldConfig{
Name: "abstract",
Type: "TEXTAREA",
Description: "Paper abstract",
},
il.DateFieldConfig{
Name: "published_date",
Type: "DATE",
Description: "Publication date of the paper",
},
il.ArrayFieldConfig{
Name: "keywords",
Type: "ARRAY",
Description: "Subject keywords or tags",
Fields: []any{
il.TextFieldConfig{
Name: "keyword",
Type: "TEXT",
Description: "A keyword or topic tag",
},
},
},
},
},
})
if err != nil {
panic(err)
}
_ = result
}
{
"name": "Extract Academic Paper Metadata",
"nodes": [
{
"parameters": {
"content": "## Extract Academic Paper Metadata\n\nResearch teams and academic platforms use this recipe to extract metadata from a paper. Upload a PDF paper and receive structured JSON with title, authors, abstract, publication date, and keywords \u2014 ready for indexing, citation analysis, or a literature review tool.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "2e5849ad-7140-4898-9adc-b818ae2d3de8",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Extract Data\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
475,
100
],
"id": "0895d89d-fcc2-409b-a989-35d4344b4b0d",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentExtraction",
"schemaInputMode": "rawJson",
"schemaJson": "{\"fields\":[{\"name\":\"title\",\"type\":\"TEXT\",\"description\":\"Title of the academic paper\"},{\"name\":\"authors\",\"type\":\"ARRAY\",\"description\":\"List of paper authors\",\"fields\":[{\"name\":\"name\",\"type\":\"TEXT\",\"description\":\"Full name of the author\"}]},{\"name\":\"abstract\",\"type\":\"TEXTAREA\",\"description\":\"Paper abstract\"},{\"name\":\"published_date\",\"type\":\"DATE\",\"description\":\"Publication date of the paper\"},{\"name\":\"keywords\",\"type\":\"ARRAY\",\"description\":\"Subject keywords or tags\",\"fields\":[{\"name\":\"keyword\",\"type\":\"TEXT\",\"description\":\"A keyword or topic tag\"}]}]}",
"files": {
"fileValues": [
{
"fileInputMode": "url",
"fileName": "paper.pdf",
"fileUrl": "https://example.com/papers/research-paper.pdf"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
"name": "Extract Data",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Extract Data",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Extract metadata from the academic paper at [file URL]. Use the extract_document tool with these fields:
- title (TEXT): Title of the academic paper
- authors (ARRAY): Each with name (TEXT)
- abstract (TEXTAREA): Paper abstract
- published_date (DATE): Publication date of the paper
- keywords (ARRAY): Each with keyword (TEXT)
Response
{
"success": true,
"data": {
"title": {
"value": "Attention Is All You Need",
"confidence": 0.99,
"citations": ["Attention Is All You Need"]
},
"authors": {
"value": [
{
"name": {
"value": "Ashish Vaswani",
"confidence": 0.98,
"citations": ["Ashish Vaswani"]
}
},
{
"name": {
"value": "Noam Shazeer",
"confidence": 0.97,
"citations": ["Noam Shazeer"]
}
}
],
"confidence": 0.97,
"citations": []
},
"abstract": {
"value": "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms.",
"confidence": 0.95,
"citations": [
"The dominant sequence transduction models are based on complex recurrent or convolutional neural networks"
]
},
"published_date": {
"value": "2017-06-12",
"confidence": 0.94,
"citations": ["12 Jun 2017"]
},
"keywords": {
"value": [
{
"keyword": {
"value": "transformer",
"confidence": 0.96,
"citations": ["Transformer"]
}
},
{
"keyword": {
"value": "attention mechanism",
"confidence": 0.95,
"citations": ["attention mechanisms"]
}
}
],
"confidence": 0.95,
"citations": []
}
}
}