paper-context-resolver

Name: paper-context-resolver
Availability: InStock
Author: teng

Resolve dataset splits, preprocessing, and evaluation protocols from primary paper sources.

2|Updated May 7, 2026

Search Tags:#paper analysis #README-first #AI repository #reproduction support #dataset details

Ready to run

npx skills add https://github.com/Teng-bio/codex-skills-hub --skill paper-context-resolver-teng-bio

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: paper-context-resolver
Source: https://github.com/Teng-bio/codex-skills-hub/tree/main/skills/global/paper-context-resolver
Command: npx skills add https://github.com/Teng-bio/codex-skills-hub --skill paper-context-resolver-teng-bio

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill fills in narrow reproduction-critical gaps in README-first AI repositories by resolving specific paper details such as dataset splits, preprocessing, evaluation protocols, checkpoint mappings, or runtime assumptions.

Core Features & Use Cases

Paper Detail Resolution: Extracts and resolves specific details like dataset splits, preprocessing, evaluation protocols, checkpoint mappings, or runtime assumptions from primary paper sources.
README-First Support: Enhances README-first AI repositories by providing evidence to fill in gaps that the README does not cover.
Conflict Recording: Records any discrepancies between README content and the paper details.

Quick Start

Use the paper-context-resolver skill to resolve the dataset split detail from the paper linked in the README.

Frequently Asked Questions about paper-context-resolver

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

FAQPage Schema

How do I resolve missing dataset split details for an AI repository reproduction?▼

To resolve missing dataset split details for an AI repository reproduction, you extract evidence from primary paper sources to fill README gaps. This provides exact preprocessing, evaluation protocols, and checkpoint mappings needed for unblocking reproduction.

What is the best way to find evaluation protocols when a README lacks reproduction instructions?▼

Finding evaluation protocols when a README lacks reproduction instructions involves resolving specific paper details from primary sources. This targets narrow reproduction-critical gaps like runtime assumptions and checkpoint mappings to provide evidence-based clarification.

How do I check for conflicts between a README and the original paper's preprocessing steps?▼

To check for conflicts between a README and original paper preprocessing steps, you resolve paper details and record discrepancies. This highlights contradictions between README content and primary paper sources to prevent reproduction failures.

Can I extract runtime assumptions from a paper to unblock AI repository reproduction?▼

Yes, you can extract runtime assumptions from primary paper sources to unblock AI repository reproduction. This resolves specific details missing from README-first repositories by providing direct evidence from the paper to fill critical gaps.

When do I need to resolve paper details for a README-first AI repository?▼

You need to resolve paper details for a README-first AI repository when the README lacks critical reproduction information. This unblocks reproduction by extracting dataset splits, preprocessing steps, and checkpoint mappings directly from primary paper sources.