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drewid74
drewid74COMMUNITY
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ai-innovation-radar

Convert AI innovation signals into project-specific recommendations with a Disruption-to-Value Test.

8|1|Updated Mar 30, 2026
Search Tags:#strategy#technology evaluation#portfolio planning#evidence-based decisions#ai innovation#self-hostable tooling#homelab mcp
One-click install
npx skills add https://github.com/drewid74/ai_skills --skill ai-innovation-radar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-innovation-radar
Source: https://github.com/drewid74/ai_skills/tree/main/ai-innovation-radar
Command: npx skills add https://github.com/drewid74/ai_skills --skill ai-innovation-radar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill converts scattered AI innovation inputs (articles, Perplexity batches, and tool findings) into actionable decisions that match your active projects and current build priorities, reducing hype and wasted exploration.

Core Features & Use Cases

  • Signal-to-decision routing: Automatically selects an operating mode (Drop, Briefing, Build, Survey, Horizon) based on your trigger phrasing and input context.
  • Structured innovation evaluation: Applies an evidence-first Disruption-to-Value Test to filter noise and produce a consistent verdict per finding (e.g., keep building vs pause and adopt).
  • Project-aware output + logging: Maps findings to affected projects, updates project STATUS files, maintains a ranked PRIORITY_QUEUE, and records session outcomes for later review.
  • Dated landscape scans and horizon tracking: Writes SURVEY and macro HORIZON entries to keep your portfolio aligned with self-hostable, Dev Island–compatible innovations.

Quick Start

Ask the AI: “Drop a Perplexity batch of AI tool findings and evaluate which ones we should integrate into Panopticon, Dev Island, and Symphony, updating PRIORITY_QUEUE and OUTCOMES.”

Frequently Asked Questions about ai-innovation-radar

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

FAQPage Schema
How do I turn AI innovation signals into actionable portfolio decisions?▼

AI innovation signals are transformed into actionable decisions by routing inputs through a multi-layer Disruption-to-Value Test, mapping evidence-based findings directly to active projects and updating priority queues.

How do I evaluate which AI tools to integrate into my active projects?▼

Evaluating AI tools for integration involves applying an evidence-first Disruption-to-Value Test to filter noise, producing a consistent verdict like keep building versus pause and adopt for each finding.

What is the best way to track AI macro horizon trends for portfolio planning?▼

Tracking AI macro horizon trends for portfolio planning requires running horizon mode scans that write dated landscape and survey entries to keep project portfolios aligned with self-hostable innovations.

Can I use Perplexity batches for evidence-based technology evaluation?▼

Perplexity batches can be dropped directly into the system for evidence-based technology evaluation, automatically filtering noise and mapping the structured findings to your specific build priorities.

Does portfolio planning work with self-hostable tooling and homelab environments?▼

Portfolio planning supports self-hostable tooling and homelab environments by scanning new project landscapes and tracking macro trends specifically for Dev Island–compatible innovations.

When should I not use automated signal routing for project briefings?▼

Automated signal routing for project briefings should not be used when incoming inputs lack sufficient context for the Disruption-to-Value Test, as applying the multi-layer filter to unstructured noise yields inconsistent verdicts.

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