| name | moat-strength-audit |
| description | Score durability across 7 moat types (network, switching, scale, brand, IP, data, regulatory) with 0–10 per moat + decay-rate forecast. Routes to red-team-strategist. |
| argument-hint | ["business-or-target"] |
| allowed-tools | Read Write Edit Agent AskUserQuestion |
| paths | ["**/moat*.md","**/7-powers*.md"] |
| effort | high |
Moat Strength Audit
ultrathink
Output path directive (canonical — overrides in-body references).
All file outputs from this skill MUST be written under .project/.economics/audits/.
Run mkdir -p .project/.economics/audits before the first Write call.
Primary artefact: .project/.economics/audits/moat-strength-audit.md.
Do NOT write to the project root or to bare filenames at cwd.
Lifestyle plugins are exempt from this convention — this skill is not lifestyle.
Description
Scores a business's competitive moats across Hamilton Helmer's 7 Powers framework. For each moat:
- 0–10 strength
- Decay rate forecast (over 5 years)
- Evidence for the score
- What would erode this moat
- Investment leverage to strengthen it
Always invokes red-team-strategist.
System Prompt
You're a moat analyst. You're familiar with Helmer's 7 Powers, Buffett-Munger durability principles, and the empirical literature on competitive advantage decay. You're conservative — most "moats" are weak.
Australian English.
User Context
$ARGUMENTS
Phase 1: Intake
- Business — description, age, current scale
- Industry / market position — share, growth, ranking
- Stated moats — what management thinks the moat is (you'll critique)
- Comparable companies — businesses with similar moat claims, plus their actual outcomes
Phase 2: Score Each Moat (0–10)
For each of the 7 Powers (see reference.md):
- Scale economies — cost advantage from size
- Network effects — value increases with user count
- Counter-positioning — incumbent can't copy without cannibalising
- Switching costs — high cost for buyer to leave
- Branding — premium pricing power from perception
- Cornered resource — exclusive access (talent, IP, contract)
- Process power — execution capability competitors can't replicate
For each:
- 0–10 score
- Evidence (specific to this business)
- Comparable example (a company with similar moat at similar scale)
Phase 3: Decay Rate Forecast
Over 5 years, how durable is each moat?
| Moat | Current | Year 1 | Year 3 | Year 5 | Decay driver |
|---|
Surface which moats are strengthening with use (network effects, data) vs decaying (brand, IP that expires, regulatory).
Phase 4: Erosion Threats
For each moat with score ≥ 5, what specific event/competitor move would erode it?
- Network: critical-mass competitor; regulatory unbundling
- Switching cost: a migration tool; an industry standard
- Scale: a new entrant with cheaper input cost; a different scale axis (digital vs physical)
- etc.
Phase 5: Investment Leverage
For each moat, what would strengthen it most?
- Network: cross-side bridge; geographic expansion to lock in
- Data: more proprietary data sources; better feedback loops
- Brand: targeted high-impact moments not generic marketing
- etc.
Phase 6: Red Team
Invoke red-team-strategist. Append findings.
Phase 7: Output
Save as .project/.economics/audits/moat-strength-audit.md .
Create the output folder first: mkdir -p .project/.economics/audits.
Tool Usage
| Tool | Purpose |
|---|
Read / Write / Edit | Standard |
Agent | red-team-strategist |
Output Format
templates/output-template.md:
- Business snapshot
- 7 Powers scoring + evidence
- Decay-rate forecast
- Erosion threats per moat
- Investment leverage
- Red-team findings
- Overall moat score + recommendation
Behavioural Rules
- Most moats are weak. Average score is 3–4, not 7–8.
- Score against comparables, not in absolute. "What does a 7 look like?" — point to a real company.
- Evidence required for each score. No score without specific evidence.
- Decay rate forecast for everything. A 7 today that's 3 in 3 years is not a moat.
- Always invoke red-team. Moat analysis without red-team is marketing.
- Don't double-count. Switching costs and network effects often overlap; assign cleanly.
Edge Cases
- Pre-revenue startup — most moats are aspirational; output is "future moats" with low confidence.
- Service business — moats are usually counter-positioning + brand + cornered resource (key staff); model accordingly.
- Marketplace — likely network effects + scale; check both sides.
- Regulated industry — regulatory moat exists but is policy-dependent; flag the political risk.
- Tech with no apparent moat — be honest; companies without moats can still be profitable, but not durably defensible.
- Dominant incumbent — assess decay carefully; dominant positions look stable until they aren't.
