PAIUpgrade

Identify upgrade opportunities and map them to PAI components from Thread 0 inventory.

1|Updated Jun 10, 2026
One-click install
npx skills add https://github.com/starlink-awaken/pai-universal --skill paiupgrade-starlink-awaken
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: PAIUpgrade
Source: https://github.com/starlink-awaken/pai-universal/tree/main/templates/packs/PAIUpgrade/src
Command: npx skills add https://github.com/starlink-awaken/pai-universal --skill paiupgrade-starlink-awaken

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

PAIUpgrade identifies and ranks upgrade opportunities for the PAI framework by correlating internal reflections, user TELOS context, and external signals into structured, executable techniques.

Core Features & Use Cases

  • Multi-thread analysis: Prior-Work Audit, User Context, Source Collection, and Internal Reflections converge into actionable upgrade candidates.
  • Prior Status gating: All recommendations are traced to Thread 0 evidence to ensure novelty and prevent repeats.
  • Canonical outputs: Produces Discoveries, Recommendations, Technique Details, Internal Reflections, Summary, Skipped Content, and Sources Processed in a single report.
  • Actionable integration: Each technique maps to a PAI component (Algorithm, Skills, Hooks, or Config) and includes concrete before/after steps.
  • Use Case: When the PAI Algorithm needs improvement, run PAIUpgrade to surface prioritized upgrade steps with evidence.

Quick Start

Run the PAIUpgrade workflow with your upgrade goal to start generating prioritized upgrade recommendations.

Frequently Asked Questions about PAIUpgrade

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

FAQPage Schema
How do I identify and prioritize framework upgrades for my algorithm?▼

PAIUpgrade identifies upgrade opportunities by correlating internal reflections, user TELOS context, and external signals into structured, executable techniques. It maps these techniques to specific components like Algorithm, Skills, Hooks, or ISA with concrete before and after steps.

What is the best way to prevent duplicate upgrade recommendations?▼

PAIUpgrade uses Prior Status gating to trace all recommendations to Thread 0 inventory evidence, ensuring novelty and preventing repeated upgrade suggestions across iterations.

How do I generate an actionable upgrade report with canonical output?▼

Run the PAIUpgrade workflow with your upgrade goal to generate a canonical report. The output includes Discoveries, Recommendations, Technique Details, Internal Reflections, Summary, Skipped Content, and Sources Processed sections.

Can I map upgrade opportunities to specific components like Hooks and ISA?▼

Yes, PAIUpgrade maps identified upgrade opportunities directly to PAI components including Algorithm, Skills, Hooks, and Config. Each technique includes concrete before and after steps for actionable integration.

How does multi-thread analysis work for algorithm improvement?▼

PAIUpgrade aggregates signals from four threads: Prior-Work Audit, User Context, Source Collection, and Internal Reflections. These converge into actionable upgrade candidates mapped to framework components.

Do I need a Thread 0 inventory before running PAIUpgrade?▼

Yes, PAIUpgrade requires a Thread 0 inventory to map upgrade opportunities and trace recommendations. Prior Status gating uses this inventory to ensure all suggestions are novel and traceable to existing evidence.