skills.rest
Cloud-Byte-Consulting
Cloud-Byte-ConsultingOFFICIAL
Explore all skills by this author →
GitHub

consumer-ai-anticipation-gap-scorecard

Diagnose consumer AI products against anticipation gap, trust ladder, and prosumer bridge frameworks.

Updated Jul 16, 2026
Search Tags:#ai agents#product strategy#gap analysis#scorecard#product diagnostic#consumer ai#trust ladder
One-click install
npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill consumer-ai-anticipation-gap-scorecard-cloud-byte-consulting
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: consumer-ai-anticipation-gap-scorecard
Source: https://github.com/Cloud-Byte-Consulting/plugins/tree/main/prompt-workflows/skills/consumer-ai-anticipation-gap-scorecard
Command: npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill consumer-ai-anticipation-gap-scorecard-cloud-byte-consulting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Product teams building consumer AI agents often lack an honest, structured read on why their product stalls below breakout adoption. This Skill runs a rigorous diagnostic that scores a product against the structural requirements for a breakaway consumer agent, replacing optimistic self-assessment with evidence-based gap analysis. ## Core Features & Use Cases - Four Problems Scorecard: Scores context, reliability, permission, and judgment maturity on a 0-3 scale with evidence and gaps. - Trust Ladder & Prosumer Bridge Assessment: Places the product on the five-step trust ladder (read, suggest, draft, act with confirmation, act autonomously) and evaluates the adoption path through professional or direct consumer entry. - Coding Agent Contrast: Benchmarks the product's domain against the five conditions (verifiability, bounded scope, domain literacy, error correction speed, task complexity) that enabled coding agents to break through. - Use Case: A founder building a proactive AI assistant uses this diagnostic to discover that reliability on long-tail tasks is the binding constraint, then receives three ranked moves to close the gap before the next funding milestone. ## Quick Start Use the consumer-ai-anticipation-gap-scorecard skill to score my consumer AI product against the anticipation gap framework.

Frequently Asked Questions about consumer-ai-anticipation-gap-scorecard

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

FAQPage Schema
How do I evaluate why my consumer AI product is not growing?▼

Run a structured diagnostic that scores the product on context access, reliability, permission design, and judgment, then places it on the five-step trust ladder. The output names the single binding constraint blocking breakout and ranks the three highest-leverage fixes.

What is the anticipation gap framework for consumer AI?▼

The anticipation gap framework evaluates consumer AI products across four problems (context, reliability, permission, judgment), a five-step trust ladder from read access to autonomous action, and a prosumer bridge assessing whether professional use can fund consumer adoption.

What information do I need to provide for the product diagnostic?▼

You need to describe what the product does, how users interact with it, what context it accesses, what actions it can take, whether it is reactive or proactive, current user metrics if available, and your core thesis. Vague answers trigger follow-up questions before scoring.

Can this diagnostic compare my product to coding agents?▼

Yes, the Coding Agent Contrast scores your domain against five conditions that enabled coding agent breakout: verifiability, bounded scope, domain literacy, error correction speed, and task complexity. For each missing condition, it identifies how the design compensates or fails to.

When should I not use a scorecard-style product diagnostic?▼

Avoid it when you lack basic product facts, since the diagnostic refuses to guess at capabilities and will stall on missing information. It also does not replace quantitative user research or cohort analysis for validating retention hypotheses.

Related Skills

Explore More Product & Management Skills→
rachmadidenirachmadideni

jobs-to-be-done

Analyze customer purchase motivations using the Jobs to Be Done framework.

Community
Intermediate
augustoheissaugustoheiss

agency-product-manager

Translate ambiguous business problems into validated product plans and PRDs.

Community
Advanced
basmawebinfo-hubbasmawebinfo-hub

UX Researcher

Designs and analyzes user research to validate product and design decisions using behavioral evidence.

Community
Advanced
RefoundAIRefoundAI
1.3k

measuring-pmf

Assess product-market fit using retention benchmarks, surveys, and organic growth signals.

Official
Intermediate