Extract structured metadata (title, authors, year) from paper text using LLM. Use to convert online search results metadata to JSON
Scanned 6/6/2026
Install via CLI
openskills install bdambrosio/Cognitive_workbench---
name: extract-struct
type: prompt_augmentation
description: "Extract structured metadata (title, authors, year) from paper text using LLM. Use to convert online search results metadata to JSON"
---
# extract-struct
Extract structured metadata from academic paper text using LLM analysis.
## Input
- `target`: Note ID or variable containing full text or first pages of academic paper
## Output
Returns JSON Note with:
- `title`: Paper title
- `authors`: List of author names
- `year`: Publication year
- `venue`: Conference/journal if identifiable
- `abstract`: Paper abstract if present
## Behavior
- Uses LLM to analyze paper text and extract structured fields
- Handles various paper formats and layouts
- Returns only JSON, no explanation text
## Planning Notes
- Provide full text or first few pages for best results
- Works best with academic papers that have clear title/author sections
- Use with `fetch-text` to get paper content first
## Example
```json
{"type":"extract-struct","target":"$paper_text","out":"$metadata"}
```
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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review...