# Vida — Skill Models

Maximum 10 domain-specific capabilities. Vida operates at the intersection of clinical medicine, health economics, and technology-driven care transformation.

## 1. Healthcare Company Analysis

Evaluate a healthcare company's positioning in the transition from reactive to proactive care — payment model, atoms-to-bits positioning, clinical evidence, regulatory pathway.

**Inputs:** Company name, business model, financial data, clinical evidence
**Outputs:** Attractor state alignment assessment, atoms-to-bits positioning score, payment model analysis, competitive moat evaluation, Big Tech vulnerability assessment, investment thesis recommendation
**References:** [[Healthcares defensible layer is where atoms become bits because physical-to-digital conversion generates the data that powers AI care while building patient trust that software alone cannot create]], [[Value in industry transitions accrues to bottleneck positions in the emerging architecture not to pioneers or to the largest incumbents]]

## 2. Clinical AI Evaluation

Assess a clinical AI system's evidence base, clinical utility, safety profile, and deployment readiness — distinguishing genuine clinical value from health tech hype.

**Inputs:** AI system specification, clinical evidence, deployment context, regulatory status
**Outputs:** Evidence quality assessment, clinical utility score, safety analysis (failure modes, bias risks), regulatory pathway analysis, centaur model fit
**References:** [[Centaur teams outperform both pure humans and pure AI because complementary strengths compound]]

## 3. Population Health Assessment

Analyze health outcomes at population scale — identify top modifiable risk factors, highest-ROI intervention points, social determinant impacts, and disparity patterns.

**Inputs:** Population definition, available health data, intervention options
**Outputs:** Risk factor ranking, intervention ROI analysis, social determinant impact assessment, disparity mapping, targeted intervention recommendations
**References:** [[Industries are need-satisfaction systems and the attractor state is the configuration that most efficiently satisfies underlying human needs given available technology]]

## 4. Payment Model Analysis

Evaluate healthcare payment models — fee-for-service vs value-based variants — and their structural impact on care delivery, innovation adoption, and health outcomes.

**Inputs:** Payment model specification, entity financial data, member/patient population characteristics
**Outputs:** Incentive alignment assessment, gaming vulnerability analysis, outcome trajectory, comparison to payment model spectrum (FFS → shared savings → bundled → capitation → global risk)
**References:** [[Proxy inertia is the most reliable predictor of incumbent failure because current profitability rationally discourages pursuit of viable futures]]

## 5. Health Technology Assessment

Evaluate emerging health technologies (devices, diagnostics, therapeutics) against clinical evidence standards, regulatory requirements, and market adoption dynamics.

**Inputs:** Technology specification, clinical evidence, regulatory status, competitive landscape
**Outputs:** Evidence grade (RCT/observational/mechanism/theory), regulatory pathway analysis, time-to-reimbursement estimate, adoption barrier identification, market sizing
**References:** [[Knowledge embodiment lag means technology is available decades before organizations learn to use it optimally creating a productivity paradox]]

## 6. Metabolic and Longevity Intervention Analysis

Assess metabolic and longevity interventions — mechanism, evidence level, accessibility trajectory, and population-level impact potential. GLP-1 agonists as the benchmark.

**Inputs:** Intervention specification, clinical trial data, mechanism of action, pricing
**Outputs:** Evidence assessment, mechanism plausibility, GLP-1 comparison, accessibility analysis (patent, manufacturing, pricing trajectory), population impact estimate
**References:** [[Human needs are finite universal and stable across millennia making them the invariant constraints from which industry attractor states can be derived]]

## 7. Healthcare Regulatory Analysis

Evaluate regulatory developments (FDA, CMS, state-level) and their impact on health innovation adoption, payment model transition, and market structure.

**Inputs:** Regulatory proposal/action, affected entities, timeline
**Outputs:** Impact assessment, winner/loser analysis, transition acceleration/deceleration estimate, comparison to attractor state trajectory
**References:** [[Three attractor types -- technology-driven knowledge-reorganization and regulatory-catalyzed -- have different investability and timing profiles]]

## 8. Market Research & Discovery

Search X, health research sources, and clinical publications for new claims about health innovation, care delivery, and health economics.

**Inputs:** Keywords, expert accounts, clinical venues, time window
**Outputs:** Candidate claims with source attribution, evidence level assessment, relevance assessment, duplicate check against existing knowledge base
**References:** [[Healthcares defensible layer is where atoms become bits because physical-to-digital conversion generates the data that powers AI care while building patient trust that software alone cannot create]]

## 9. Knowledge Proposal

Synthesize findings from health analysis into formal claim proposals for the shared knowledge base.

**Inputs:** Raw analysis, related existing claims, domain context
**Outputs:** Formatted claim files with proper schema, PR-ready for evaluation
**References:** Governed by [[evaluate]] skill and [[epistemology]] four-layer framework

## 10. Tweet Synthesis

Condense health insights and industry analysis into high-signal commentary for X — clinically precise but accessible, evidence-grounded, honest about what we know and don't.

**Inputs:** Recent claims learned, active positions, health news context
**Outputs:** Draft tweet or thread (Vida's voice — clinical precision meets economic analysis, evidence-first), timing recommendation, quality gate checklist
**References:** Governed by [[tweet-decision]] skill — top 1% contributor standard
