moatmri

Project ManagementSafeClaude Codex

How to Install

This skill comes from a community source. Check the original listing for install instructions.

General Claude Code install: copy SKILL.md to ~/.claude/skills/

MoatMRI — AI Disruption Pressure Analysis

Where does intelligence pressure break this system first?

When to Use This Skill

"Is my business at risk from AI? 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?"
"I'm doing due diligence on [company] — what's their AI displacement risk?"
"Where does my competitive moat actually hold against AI pressure?"

How It Works

Step 1 — Gather Inputs

Ask if not provided: - Industry (e.g., "real estate", "community banking", "retail pharmacy", "law firm") - Entity type (e.g., "independent broker", "solo practitioner", "regional franchise") - Target name (optional — specific organization for named analysis)

Limitations

Produces strategic risk analysis, not audited market research or investment advice.
Depends on current company, market, regulatory, and competitive context supplied by the user or gathered from reliable sources.
Treats disruption scenarios as planning tools; scores should be revisited as new evidence appears.

Step 2 — 10-Vector Pressure Map

Score AI disruption pressure across exactly these 10 vectors (0–10):

#	Vector	What to Measure
1	labor_substitution	Which roles/functions are directly automatable
2	customer_interface	How AI changes how customers reach this entity
3	knowledge_commoditization	Does AI commoditize the expertise this entity sells
4	pricing_pressure	Does AI enable lower-cost competitors to undercut
5	supply_chain_automation	Does AI change input costs or supplier relationships
6	data_moat	Does this entity have proprietary data AI can't replicate
7	trust_relationship_moat	How much does customer loyalty protect against displacement
8	distribution_channel_disruption	Does AI create new channels that bypass this entity
9	regulatory_compliance_exposure	Does AI alter the regulatory or liability landscape
10	decision_speed_gap	Does AI accelerate decisions in ways that disadvantage this entity

For each vector produce: score, headline, near_term (12 months), far_term (3 years).

Aggregate risk score: mean of all 10 vectors. Flag any vector ≥ 7 as critical.

Step 3 — AI Front-Door Takeover Storyboard

6-step narrative of how an AI-native competitor displaces this entity: 1. The entry point 2. The wedge (first 10% of market) 3. The acceleration (what makes it compound) 4. The tipping point (when incumbent can't recover) 5. The aftermath 6. The survivor profile

Step 4 — 90-Day Counterstrike Plan

Track A (Days 0–30): Immediate defense — what to stop, what to protect
Track B (Days 31–60): Intelligence-layer build — data/relationships to fortify
Track C (Days 61–90): Offensive positioning — use AI pressure as competitive weapon

Best Practices

✅ Score all 10 vectors before calculating aggregate — resist stopping at obvious ones
✅ Keep the storyboard specific to industry/entity, not generic disruption narrative
✅ Track C should be actionable within 90 days, not aspirational 3-year strategy
❌ Don't conflate data_moat with trust_relationship_moat — they protect differently