score-extraction
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/score-extractionExtracts structured performance scores from academic papers
- Identifies and extracts task, dataset, metric, and score information
- Uses paper content and target task filters as input
- Parses results sections, tables, and figures for context
- Returns JSON with scores, baselines, and confidence level
SKILL.md
.github/skills/score-extractionView on GitHub ↗
---
name: score-extraction
description: Extract (Task, Dataset, Metric, Score, Conditions) tuples from a paper
execution: subagent
prompt: ./prompt.md
input: paper_content, target_tasks
used-by: baseline-establishment
---
# Score Extraction
## Purpose
Parse a paper's results sections, tables, and figures to extract all reported performance scores as structured tuples. Each tuple captures the full context needed for fair comparison: what was measured, on what data, under what conditions.
## Input Schema
| Field | Type | Description |
|-------|------|-------------|
| paper_content | string | Full paper text (markdown format) |
| target_tasks | string[] | Tasks to focus extraction on (empty = extract all) |
## Output Schema
```json
{
"paper_title": "string",
"scores": [
{
"method": "string",
"task": "string",
"dataset": "string",
"split": "test|val|dev|train",
"metric": "string",
"score": 0.0,
"score_std": null,
"num_runs": null,
"is_primary_result": true,
"is_ablation": false,
"table_reference": "string",
"notes": "string"
}
],
"baselines_reported": ["string"],
"extraction_confidence": "high|medium|low"
}
```