GRADE-on-Ingest

Assess GRADE quality of new research sources upon corpus ingestion.

175|26|Updated Aug 14, 2025
One-click install
npx skills add https://github.com/jmagly/aiwg --skill grade-on-ingest-jmagly
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: GRADE-on-Ingest
Source: https://github.com/jmagly/aiwg/tree/main/plugins/sdlc/skills/grade-on-ingest
Command: npx skills add https://github.com/jmagly/aiwg --skill grade-on-ingest-jmagly

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of assessing the quality of research sources as they are added to a corpus, preventing unassessed or low-quality sources from being used without proper context.

Core Features & Use Cases

  • Automated Quality Assessment: Assigns a baseline GRADE quality level to new research sources upon ingestion.
  • Corpus Quality Monitoring: Tracks the percentage of assessed sources and flags if it drops below acceptable thresholds.
  • Use Case: When a new scientific paper is added to your research repository, this Skill automatically determines its initial quality (e.g., HIGH for peer-reviewed journals, LOW for blog posts) and flags it for further review if necessary, ensuring all cited material meets a minimum standard.

Quick Start

Automatically assess the quality of any new research source added to the corpus.

Frequently Asked Questions about GRADE-on-Ingest

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

FAQPage Schema
How do I automate source validation and quality assessment for new research corpus ingestion?

Automated source validation triggers a GRADE quality assessment upon research ingestion, extracting metadata to determine a baseline quality level based on source type. It automatically assigns initial quality grades and flags low-quality sources for further review.

What is the GRADE approach for evidence synthesis and how does it work during corpus management?

The GRADE approach for evidence synthesis evaluates source quality by extracting metadata upon ingestion and determining a baseline level based on source type. It then invokes a Quality Assessor agent to perform a full assessment and update the corpus index.

How do I prevent unassessed or low-quality research sources from being used in evidence synthesis?

To prevent unassessed sources from being used, this process automatically assesses research quality at ingestion, tracks the percentage of assessed sources, and sends notifications when low-quality sources are added or assessment levels drop below thresholds.

Can I monitor corpus quality and flag low percentage thresholds for research source validation?

Yes, corpus quality monitoring tracks the percentage of assessed research sources and flags the corpus if the assessed percentage drops below acceptable thresholds. This ensures continuous quality control during evidence synthesis and research ingestion.

Does the automated quality assessment assign different baseline levels for peer-reviewed papers versus blog posts?

Yes, the automated quality assessment determines a baseline GRADE level based on source type, assigning higher quality levels to peer-reviewed journals and lower levels to sources like blog posts. Low-quality sources are subsequently flagged for further review.

What happens after a Quality Assessor agent performs a full assessment on an ingested research source?

After the Quality Assessor agent performs a full GRADE assessment, the evaluation results are stored and the corpus index is updated. Notifications are automatically sent out for any sources determined to be low-quality.