Assess AI disruption risk across 10 competitive vectors

Runs a structured AI-disruption pressure analysis for a specific business, industry, or entity type. It scores 10 fixed vectors (0-10 each) - labor substitution, customer interface, knowledge commoditization, pricing pressure, supply chain automation, data moat, trust/relationship moat, distribution channel disruption, regulatory compliance exposure, and decision speed gap - producing a score, headline, 12-month near-term outlook, and 3-year far-term outlook for each vector, then averages all 10 into an aggregate risk score and flags any vector scoring 7 or higher as critical. It then builds a 6-step AI front-door takeover storyboard (entry point, wedge, acceleration, tipping point, aftermath, survivor profile) narrating how an AI-native competitor could displace the entity, and closes with a 90-day counterstrike plan split into three tracks: Track A (days 0-30, immediate defense - what to stop, what to protect), Track B (days 31-60, intelligence-layer build - data and relationships to fortify), and Track C (days 61-90, offensive positioning that turns AI pressure into a competitive weapon).

Use it for questions like "is my business at risk from AI, and where am I most exposed", "how would an AI-native startup take over my market", "what should I do in the next 90 days to defend against AI disruption", AI-displacement due diligence on a specific company, or "where does my competitive moat actually hold against AI pressure". It produces strategic risk analysis, not audited market research or investment advice, and depends on the current company, market, regulatory, and competitive context the user supplies or that can be reliably gathered - scores should be revisited as new evidence appears, not treated as fixed. Best practice is to score all 10 vectors before calculating the aggregate rather than stopping at the obvious ones, keep the storyboard specific to the industry and entity rather than a generic disruption narrative, keep Track C actionable within 90 days rather than an aspirational 3-year strategy, and avoid conflating data_moat with trust_relationship_moat since they protect the entity differently.

Inputs are the industry (for example real estate, community banking, retail pharmacy, or a law firm), entity type (for example independent broker, solo practitioner, or regional franchise), and optionally a specific target organization name, gathered by the skill if not already provided. Outputs are the 10-vector pressure map with its aggregate score and critical-vector flags, the 6-step takeover storyboard, and the 90-day three-track counterstrike plan.

MoatMRI is a self-contained analytical skill with no live API integrations. A companion full "bring your own key" tool built on the same methodology is hosted separately by the source repository's author, and the skill itself is MIT-licensed, built by IntuiTek1.

Founders, operators, consultants, and investors who need a structured, repeatable way to score AI-disruption exposure across ten distinct pressure vectors, tell a concrete story of how a competitor could exploit that exposure, and turn it into a 90-day defensive-then-offensive action plan, rather than a generic AI-will-disrupt-everything narrative.