content-refinement-agent

Iteratively simulate peer review and revise LaTeX paper drafts with accept/revert control.

2|1|Updated Apr 19, 2026
One-click install
npx skills add https://github.com/raja21068/AutoResearch --skill content-refinement-agent-raja21068
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: content-refinement-agent
Source: https://github.com/raja21068/AutoResearch/tree/main/skills/paper-pipeline/content-refinement-agent
Command: npx skills add https://github.com/raja21068/AutoResearch --skill content-refinement-agent-raja21068

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you turn an initial LaTeX paper draft into a stronger, publication-ready version by iteratively simulating peer review and applying targeted revisions while strictly enforcing accept/revert halt rules.

Core Features & Use Cases

  • Simulated peer review: Generates structured strengths, weaknesses, questions, and axis scores using a reviewer rubric designed for conservative feedback.
  • Targeted LaTeX revisions: Applies revisions guided by a verbatim Content Refinement Agent prompt while integrating reviewer questions into the manuscript text.
  • Execution-grounded iteration control: Snapshots each iteration, recompiles with LaTeX, re-scores, and either accepts or reverts based on deterministic scoring/plateau logic to prevent score gaming.

Use case example: You have a draft in workspace/drafts/paper.tex and you want to improve scientific depth, technical execution, and evidence presentation by running 3 refinement iterations with real compile+score feedback, then promoting the best accepted snapshot to workspace/final/paper.tex.

Quick Start

Refine the current draft by delegating Step 5 when the orchestrator asks for peer-review-based content refinement, so it compiles each iteration, scores it, and promotes the best accepted snapshot.

Frequently Asked Questions about content-refinement-agent

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

FAQPage Schema
How do I iteratively peer review and improve a LaTeX research paper draft?▼

To iteratively peer review and improve a LaTeX research paper draft, this Skill simulates structured reviewer feedback, applies targeted content revisions, recompiles with latexmk, and uses deterministic scoring to accept or revert snapshots.

Can I enforce citation integrity and verify numeric claims when refining a scientific manuscript?▼

Yes, you can enforce citation integrity and verify numeric claims when refining a scientific manuscript by restricting additions to an allowed citation pool and checking all numeric claims against a provided experimental ground-truth log.

What is the best way to prevent score gaming during automated paper revisions?▼

The best way to prevent score gaming during automated paper revisions is to enforce deterministic accept or revert halt rules with early-stop behavior based on scoring plateaus after each LaTeX compilation iteration.

Does this peer review simulation work with arXiv-style manuscripts and conference guidelines?▼

Yes, this peer review simulation works with arXiv-style manuscripts and conference guidelines, applying targeted revisions guided by an experimental ground-truth log to strengthen scientific depth and technical execution.

How do I track changes across multiple iterations of scientific writing refinement?▼

To track changes across multiple iterations of scientific writing refinement, the Skill generates per-iteration review.json and score.json snapshots, allowing you to compare progress and promote the best accepted version to your final output.