paper-autoraters

Compute quality metrics and side-by-side judgments for research paper drafts.

635|88|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/Ar9av/PaperOrchestra --skill paper-autoraters
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-autoraters
Source: https://github.com/Ar9av/PaperOrchestra/tree/main/skills/paper-autoraters
Command: npx skills add https://github.com/Ar9av/PaperOrchestra --skill paper-autoraters

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates rigorous, reproducible scoring of research paper drafts so authors and evaluation pipelines can quantify literature-review quality, citation fidelity, and holistic paper quality without manual rubric application.

Core Features & Use Cases

  • Citation F1 Partitioning: Partition references into P0/P1 priority buckets and deterministically compute Precision/Recall/F1 against ground-truth via Semantic Scholar ID resolution.
  • Literature Review Quality (6-axis): Produce conservative, evidence-based 6-axis JSON scores with penalties and an overall score for Intro + Related Work.
  • Side-by-Side (SxS) Comparisons: Run dual-order SxS judgments for full-paper and literature-review-only comparisons to mitigate positional bias.
  • Use Case: Validate a paper-generating pipeline by scoring generated drafts against a ground-truth paper, compare two pipeline outputs, or audit literature-review improvements across iterations.

Quick Start

Run the autoraters to score the draft 'submission_v1.pdf' against the ground-truth 'paper_gt.pdf' and produce JSON reports.

Frequently Asked Questions about paper-autoraters

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate research paper evaluation and literature review scoring?

Automated research paper evaluation computes structured quality metrics and side-by-side judgments using four autoraters. It produces conservative 6-axis JSON scores with penalties for Intro and Related Work sections, alongside an overall score for literature review quality.

How do I calculate citation F1 score for a research paper draft?

Citation F1 score calculation partitions references into P0 and P1 priority buckets and deterministically computes Precision, Recall, and F1 against ground-truth. This process requires a host agent to resolve references to Semantic Scholar IDs before running the deterministic scoring scripts.

What is side-by-side SxS comparison for research benchmarking?

Side-by-side SxS comparison for research benchmarking runs dual-order judgments for full-paper and literature-review-only comparisons to mitigate positional bias. It validates paper-generating pipelines by scoring generated drafts against a ground-truth paper or comparing two pipeline outputs.

Can I score PDF research paper drafts without manual rubric application?

Scoring PDF research paper drafts without manual rubric application is supported, but requires a host agent to extract Introduction and Related Work sections. The host agent must also resolve references to Semantic Scholar IDs before the autoraters can compute the structured quality metrics.

Does paper evaluation work with Semantic Scholar ID resolution for citation fidelity?

Paper evaluation works with Semantic Scholar ID resolution to quantify citation fidelity accurately. The deterministic scripts use these resolved IDs to partition references into priority buckets and compute Precision, Recall, and F1 against the provided ground-truth data.