tracking-list

Score, format, and validate AI industry updates across four event types.

28|3|Updated Apr 8, 2026

Search Tags:#verification #scoring #deduplication #tracking #ai-news #timeliness #record-format

Ready to run

npx skills add https://github.com/octo-patch/MorningAI --skill tracking-list

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tracking-list
Source: https://github.com/octo-patch/MorningAI/tree/main/skills/tracking-list
Command: npx skills add https://github.com/octo-patch/MorningAI --skill tracking-list

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Unified specification for scoring, formatting, and validating AI news items across Product, Model, Benchmark, and Funding types.

Core Features & Use Cases

Defines a four-type taxonomy (Product, Model, Benchmark, Funding) with source priority rules and verification criteria.
Establishes a standardized record format and a complete workflow for data collection, scoring, deduplication, and cross-source linking.
Provides guidance for timeliness verification and multi-source corroboration to ensure reliable updates.

Quick Start

Classify the item type, verify its timeliness, and format the record using the provided template.

Frequently Asked Questions about tracking-list

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

FAQPage Schema

How do I standardize the format of AI news records from different sources?▼

To standardize AI news records, classify the item into Product, Model, Benchmark, or Funding types, then apply the provided record template. This enforces frontmatter presence and type labeling for consistent formatting across official sources, changelogs, and arXiv.

What is the best way to verify the timeliness of AI industry updates?▼

Verifying AI industry updates requires multi-source corroboration across official blogs, GitHub releases, and media. The pipeline applies deterministic scoring and source priority rules to validate timeliness and ensure reliable updates before formatting.

How do I deduplicate and score AI news items from multiple feeds?▼

Deduplicating and scoring AI news items involves a deterministic pipeline that cross-references multiple sources. It applies safety checks and scoring rules to filter redundant updates and link corroborating records across feeds.

Does this scoring specification work for both product releases and funding events?▼

Yes, the scoring specification works for product releases and funding events by using a four-type taxonomy. It applies unified verification criteria and source priority rules tailored to each specific event category.

When do I need to apply frontmatter validation to AI tracking records?▼

You need frontmatter validation when processing AI tracking records to ensure structural compliance and type labeling. The specification enforces frontmatter presence as a prerequisite for passing safety checks and entering the scoring pipeline.

Can I use this tracking list specification for updates found on arXiv?▼

Yes, you can use this tracking specification for arXiv updates. It includes arXiv in its source priority rules and applies timeliness verification and multi-source corroboration to validate research model and benchmark records.