feasibility-assessor

Business

Evaluates whether a business idea is technically buildable and financially viable. Covers unit economics (CAC, LTV), revenue modeling, break-even, and go/no-go verdicts. Triggers on: "feasibility assessment", "viability analysis", "unit economics", "build vs buy", "go/no-go decision", "ROI projection".

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Feasibility Assessor

Evaluate business ideas and features across two tracks: financial viability and technical feasibility. Produce an integrated verdict with actionable de-risking recommendations.

Phase 1: Input Classification

Determine the input type:

Idea pitch: informal description of a concept
Feature spec: defined requirements for a product addition
Repo/codebase: existing code to evaluate for extension or pivot
Business plan: structured document with financials

Extract from the input:

Value proposition (what problem it solves, for whom)
Target customer segment
Pricing intent or revenue model
Technology stack (stated or implied)
Competitive landscape awareness

If critical inputs are missing, ask targeted clarifying questions before proceeding. Minimum viable inputs: value proposition and target customer.

Phase 2: Financial Analysis

Reference: references/unit-economics.md, references/financial-viability.md

Skip this phase only when the request is purely technical (e.g., "can we build X with Y stack").

Unit Economics

Calculate Customer Acquisition Cost (CAC) — fully loaded: marketing spend + sales cost + overhead allocation per acquired customer
Calculate Customer Lifetime Value (LTV) — ARPU multiplied by average customer lifetime, adjusted for gross margin
Compute LTV:CAC ratio — minimum viable: 3:1
Determine contribution margin per unit sold or per customer served
Calculate payback period — months until cumulative gross profit from a customer exceeds CAC

State every assumption explicitly. Flag assumptions with high sensitivity (small change flips the outcome).

Revenue Modeling

Identify all revenue streams and size each one
Assess pricing strategy fit: cost-plus, value-based, competitive, freemium-to-paid
Apply conversion rate assumptions — use industry benchmarks from reference material
Model churn and retention — apply cohort decay curves where possible

Break-Even Analysis

Separate fixed costs (rent, salaries, infrastructure baseline) from variable costs (COGS, transaction fees, support per user)
Calculate break-even point in units, customers, or revenue
Model three scenarios:
- Pessimistic: 50th percentile conversion, high churn, slow growth
- Base: industry-average assumptions
- Optimistic: top-quartile performance

Path to Profitability

Project gross margin trajectory over 12-24 months
Model operating expense scaling (linear vs step-function vs economies of scale)
Estimate funding requirements and runway at current burn
Compare against industry benchmarks for time-to-profitability

Phase 3: Technical Analysis

Reference: references/technical-risk.md

Skip this phase only when the request is purely financial (e.g., "are the unit economics viable for a SaaS at $29/mo").

Architecture Assessment

Classify complexity:

Level	Description	Examples
1 — Simple	Standard CRUD, single service	Landing page, basic CMS, form-based app
2 — Moderate	Multi-service integration, auth, payments	E-commerce, SaaS dashboard, API platform
3 — Complex	Distributed systems, real-time, high availability	Marketplace, streaming platform, fintech
4 — Novel	R&D required, unproven at scale	ML-driven product, novel protocol, hardware+software

Evaluate:

Technology stack maturity and ecosystem support
Infrastructure requirements and cost scaling curve
Third-party dependency count and criticality

Build Estimation

Define MVP scope — the minimum feature set that tests the core value proposition
Estimate development timelines:
- Optimistic: experienced team, known stack, minimal unknowns
- Realistic: standard team, some learning curve, normal blockers
- Pessimistic: new domain, integration challenges, regulatory overhead
Identify required team skills and availability
Run build vs buy vs partner analysis for each major component

Risk Scoring

Score each dimension 1-5 (1 = low risk, 5 = critical risk):

Dimension	What It Measures
Technical novelty	Proven tech (1) vs active R&D required (5)
Integration complexity	Self-contained (1) vs many external APIs (5)
Scale readiness	Architecture handles 100x with config changes (1) vs requires re-architecture (5)
Data risk	Public/owned data, no regulation (1) vs restricted data, heavy compliance (5)
Security/compliance	No sensitive data (1) vs PCI/HIPAA/SOC2 required (5)

Composite technical risk = weighted average. Flag any dimension scoring 4+ as a blocker requiring mitigation plan.

Phase 4: Integrated Feasibility Score

Financial Viability

Viable: LTV:CAC > 3:1, payback < 18 months, clear path to positive unit economics
Risky: LTV:CAC 1.5-3:1, payback 18-36 months, unit economics depend on scale
Not viable: LTV:CAC < 1.5:1, payback > 36 months, negative contribution margin

Technical Feasibility

Straightforward: complexity level 1-2, all risk dimensions < 3
Challenging: complexity level 2-3, one or two dimensions at 3-4
High-risk: complexity level 3-4, multiple dimensions at 4+
Research-grade: complexity level 4, any dimension at 5

Overall Verdict

Financial	Technical	Verdict
Viable	Straightforward	Green — proceed
Viable	Challenging	Yellow — proceed with caution, mitigate tech risks
Risky	Straightforward	Yellow — validate financial assumptions first
Risky	Challenging	Yellow — high uncertainty, run cheap experiments
Not viable	Any	Red — reconsider fundamentals
Any	High-risk/Research	Red — reduce technical unknowns before committing

Assumption Sensitivity

Identify the top 3-5 assumptions that most influence the verdict. For each, state:

Current assumed value
Threshold value that would flip the assessment
How to validate cheaply

De-risking Recommendations

Rank experiments by cost-to-run vs information-value. Prioritize experiments that validate the riskiest assumptions at the lowest cost.

Phase 5: Report Generation

Structure the output as:

Executive Summary

One-paragraph verdict with go/no-go signal
Top 3 risks and top 3 strengths

Financial Dashboard (if applicable)

Unit economics table: CAC, LTV, LTV:CAC, contribution margin, payback period
Revenue projection under 3 scenarios (table or description)
Break-even point and timeline

Technical Scorecard (if applicable)

Complexity classification
Risk dimension scores (table)
MVP scope and timeline estimate
Critical dependencies and mitigation

Sensitivity Analysis

Which assumptions, if wrong, flip the verdict
Threshold values for each critical assumption

Recommended Next Steps

Ordered list of actions, cheapest validation first
Clear owners or skill requirements for each step
Decision gates: what evidence triggers proceed vs pivot vs stop