Assumption Validator

"Make hidden assumptions visible; make visible assumptions testable."

Assumptions are the invisible architecture of every decision. This skill provides a systematic methodology for surfacing, classifying, validating, and stress-testing the assumptions that underlie decisions, strategies, plans, and architectures. The output is a RISK-ASSESSMENT artifact that transforms assumption risk into actionable guidance.

1. Purpose

Core Value Proposition

Every decision rests on assumptions. Some are explicit and acknowledged. Many are implicit, hidden in the reasoning chain. The most dangerous are structural—embedded in how we frame the problem itself. This skill makes the invisible visible and the untested testable.

Capabilities

2. When to Use

Ideal Use Cases

Anti-Patterns (When NOT to Use)

3. Parameters

subject_type

validation_intensity

assumption_depth

counterfactual_analysis

confidence_threshold

time_horizon

Parameter Effects Matrix

validation_intensity: light

validation_intensity: standard

validation_intensity: rigorous

assumption_depth: explicit_only

assumption_depth: include_implicit

assumption_depth: full_structural

time_horizon: short_term

time_horizon: long_term

4. Five-Phase Workflow

Workflow Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│                         ASSUMPTION VALIDATOR                                 │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐                   │
│  │   PHASE 1    │    │   PHASE 2    │    │   PHASE 3    │                   │
│  │   Subject    │───▶│  Assumption  │───▶│Classification│                   │
│  │   Intake     │    │  Surfacing   │    │& Prioritize  │                   │
│  └──────────────┘    └──────────────┘    └──────────────┘                   │
│         │                   │                   │                            │
│         ▼                   ▼                   ▼                            │
│    [Framed         [Raw Assumption      [Prioritized                        │
│     Subject]        Inventory]           List]                              │
│                                                 │                            │
│                                                 ▼                            │
│                          ┌──────────────┐    ┌──────────────┐               │
│                          │   PHASE 5    │◀───│   PHASE 4    │               │
│                          │  Synthesis   │    │  Validation  │               │
│                          │& Risk Assess │    │& Stress Test │               │
│                          └──────────────┘    └──────────────┘               │
│                                 │                   │                        │
│                                 ▼                   ▼                        │
│                          [RISK-ASSESSMENT   [Validated/                     │
│                           CONTRACT-08]       Invalidated]                   │
│                                                                              │
└─────────────────────────────────────────────────────────────────────────────┘

Phase 1: Subject Intake & Framing

Purpose: Understand what's being validated and establish clear boundaries.

Steps:

1. Receive subject artifact

   • Accept decision document, strategy brief, plan, ADR, or proposal
   • If verbal, request written summary or create one together
   • Note: Subject should be specific enough to identify assumptions

2. Extract context metadata

   • Subject type (decision, strategy, plan, architecture, investment, product_direction)
   • Time horizon (when does this need to succeed?)
   • Stakeholders (whose assumptions might be embedded?)
   • Decision reversibility (high-stakes or easily changed?)

3. Define validation scope

   • What's in scope for assumption analysis?
   • What's explicitly out of scope?
   • Are there protected assumptions (e.g., executive mandates)?

4. Identify information sources

   • Subject document(s)
   • Supporting materials
   • Domain experts available for consultation
   • Historical precedents

5. Set validation intensity

   • Light: Quick scan, top assumptions only
   • Standard: Balanced depth and coverage
   • Rigorous: Exhaustive, all techniques applied

6. Confirm framing with stakeholder

   • "We're validating assumptions in [subject] with [intensity] intensity."
   • "Scope includes [X], excludes [Y]."
   • "Time horizon is [Z]."

Quality Gate: Subject Framed

• Subject boundaries explicitly defined
• Context metadata captured
• Validation intensity confirmed
• Information sources identified

Output: Framed subject with boundaries and context

Phase 2: Assumption Surfacing

Purpose: Extract all assumption types—explicit, implicit, and structural.

Reference: See

references/surfacing-techniques.md

Steps:

1. Scan for explicit assumptions

   • Search subject document for assumption markers:
     • "We assume...", "Given that...", "Assuming..."
     • "This depends on...", "If [condition]..."
     • "We're betting that...", "Our hypothesis is..."
   • Document verbatim with source location
   • See:

     references/assumption-taxonomy.md

     §1 (Explicit)

2. Probe for implicit assumptions

   Apply surfacing techniques based on

   assumption_depth

   :

   Technique	Question	Yields
   Inversion	"What would have to be true for this to fail?"	Hidden dependencies
   Five Whys	"Why do we believe this? Why? Why?"	Reasoning chain foundations
   Outsider Test	"What would a skeptic question first?"	Non-obvious assumptions
   Pre-mortem	"It failed. What assumption was wrong?"	Failure-mode assumptions
   Dependency Mapping	"What does this depend on?"	Upstream assumptions

   • See:

     references/surfacing-techniques.md

     for full technique protocols

3. Surface structural assumptions (if

   assumption_depth: full_structural

   )

   Technique	Question	Yields
   Frame Questioning	"Why did we frame this as X not Y?"	Framing assumptions
   Missing Voices	"Whose perspective is absent?"	Stakeholder blind spots
   Scope Boundary Probe	"Why is X out of scope?"	Scope assumptions
   Alternative Structures	"What if we organized around different dimensions?"	Structural alternatives

   • See:

     references/assumption-taxonomy.md

     §3 (Structural)

4. Document each assumption

   For each assumption captured:

   - ID: A[n]
   - Statement: [Clear, falsifiable statement]
   - Type: EXPLICIT | IMPLICIT | STRUCTURAL
   - Source: [How it was identified]
   - Initial confidence: [0.0-1.0 estimate]
   

5. Check for completeness

   • Have we covered all sections of the subject document?
   • Have we applied minimum techniques per intensity level?
   • Are there obvious gaps in coverage?

Quality Gates:

• All Explicit Captured: Document scan for assumption markers complete
• Implicit Probe Done: At least N surfacing techniques applied (N per intensity)
• Structural Check: Frame questioning performed (if full_structural)

Output: Raw assumption inventory (unclassified, unprioritized)

Phase 3: Classification & Prioritization

Purpose: Categorize assumptions by type and score criticality for prioritization.

Reference: See

references/load-bearing-analysis.md

Steps:

1. Assign assumption types

   Classify each assumption into one or more types:

   Type	Definition	Risk Level
   EXPLICIT	Directly stated in subject document	Low (acknowledged)
   IMPLICIT	Required for conclusions but unstated	Medium (hidden)
   STRUCTURAL	Embedded in problem framing	High (invisible)
   LOAD-BEARING	If wrong, entire edifice collapses	Critical
   CONTEXTUAL	About environment/market/conditions	Variable
   BEHAVIORAL	About how people/systems will act	Medium-High

   • See:

     references/assumption-taxonomy.md

     for detailed type definitions

2. Perform load-bearing analysis

   Score each assumption on four dimensions:

   Dimension	Scale	Question
   Dependency (D)	1-5	How many conclusions depend on this?
   Reversibility (R)	1-5	Can we recover if this is wrong?
   Validation Cost (V)	1-5	How hard is it to verify? (inverse)
   Confidence (C)	0-1	How confident are we currently?

   Priority Formula:

   Priority = (D × (1 - C)) / V
   

   High dependency, low confidence, low validation cost = highest priority

   • See:

     references/load-bearing-analysis.md

     for scoring rubrics

3. Map dependencies

   For high-priority assumptions:

   • What other assumptions depend on this one?
   • What conclusions would be invalidated if wrong?
   • Are there assumption chains (A depends on B depends on C)?

4. Identify load-bearing assumptions

   Flag assumptions where:

   • Priority score > threshold (typically 2.0)
   • OR dependency score = 5 (everything depends on it)
   • OR labeled STRUCTURAL (framing assumptions)

5. Rank and filter

   • Sort by priority score descending
   • Per intensity level:
     • Light: Top 3
     • Standard: Top 5
     • Rigorous: All with priority > 1.0

Quality Gates:

• Types Assigned: Every assumption has type classification
• Load-Bearing Identified: Top N critical assumptions flagged
• Priority Scores: All assumptions have priority scores

Output: Prioritized assumption list with scores and dependencies

Phase 4: Validation & Stress-Testing

Purpose: Test assumptions against evidence and counterfactual scenarios.

Reference: See

references/validation-methods.md

references/what-if-framework.md

Steps:

1. Select validation methods per assumption

   Match methods to assumption characteristics:

   Assumption Type	Recommended Methods
   EXPLICIT	Evidence check, Cross-validation
   IMPLICIT	Counterfactual, Expert challenge
   STRUCTURAL	Frame alternatives, Outside perspective
   CONTEXTUAL	Historical precedent, Time decay test
   BEHAVIORAL	Stakeholder interviews, Incentive analysis

   • See:

     references/validation-methods.md

     for method protocols

2. Execute evidence check

   For each prioritized assumption:

   Evidence Quality	Weight	Description
   Primary source	1.0	Direct measurement, documentation
   Secondary source	0.7	Reported by credible third party
   Expert opinion	0.6	Domain expert judgment
   Inference	0.4	Logical derivation from other facts
   Assumption	0.2	Based on another assumption

   • Document evidence found (or lack thereof)
   • Note evidence quality and source

3. Run counterfactual analysis (if

   counterfactual_analysis: true

   )

   For top load-bearing assumptions:

   WHAT-IF: [Assumption] is FALSE
   
   Immediate impacts:
   - [What breaks immediately?]
   
   Cascade effects:
   - [What else fails as a consequence?]
   
   Decision change:
   - [Would the decision/strategy change?]
   
   Impact magnitude: NEGLIGIBLE | MINOR | MODERATE | MAJOR | CATASTROPHIC
   

   • See:

     references/what-if-framework.md

     for structured protocol

4. Calibrate confidence

   Assign epistemic labels based on evidence:

   Label	Confidence	Definition
   VERIFIED	0.9-1.0	Confirmed by direct evidence
   LIKELY	0.7-0.9	Strong indirect evidence
   POSSIBLE	0.4-0.7	Some supporting evidence
   SPECULATIVE	0.1-0.4	Limited evidence, mostly inference
   UNKNOWN	0.0-0.1	Insufficient basis for judgment

   • See:

     references/confidence-calibration.md

     for calibration techniques

5. Determine validation status

   Status	Criteria
   VALIDATED	Confidence ≥ confidence_threshold , evidence quality ≥ 0.7
   PARTIAL	Some evidence, but confidence < threshold
   UNVALIDATED	No evidence found, or conflicting evidence
   INVALIDATED	Evidence contradicts assumption
   CONTESTED	Multiple sources disagree

6. Document validation results

   Per assumption:

   - Validation status: [status]
   - Confidence: [0.0-1.0]
   - Epistemic label: [label]
   - Evidence summary: [brief]
   - Counterfactual impact: [if run]
   - Validation method(s): [methods used]
   

Quality Gates:

• Top N Validated: Top assumptions have validation results
• Counterfactuals Run: What-if scenarios for load-bearing assumptions
• Confidence Calibrated: All assumptions have epistemic labels

Output: Validated/invalidated assumptions with confidence levels

Phase 5: Synthesis & Risk Assessment

Purpose: Compile findings into RISK-ASSESSMENT artifact with actionable recommendations.

Reference: See

templates/risk-assessment-output.md

Steps:

1. Derive risks from assumption status

   Transform assumption findings into risks:

   Assumption Status	Risk Derivation
   INVALIDATED	Direct risk: "Assumption X is false"
   UNVALIDATED	Risk: "Assumption X may be false (unverified)"
   CONTESTED	Risk: "Disagreement on assumption X"
   Low confidence	Risk: "Uncertain assumption X (confidence: Y)"
   High dependency + any issue	Amplified risk due to cascade

2. Score each derived risk

   Using SEVERITY-SCORING (RUBRIC-07):

   Dimension	Scale	Weight
   Impact	1-4 (low→critical)	0.5
   Likelihood	1-4 (rare→certain)	0.3
   Detectability	1-4 (obvious→hidden)	0.2

   Risk score = weighted sum

3. Develop mitigation strategies

   For high-scoring risks:

   Strategy	When to Use
   Avoid	Remove dependency on assumption (redesign)
   Transfer	Shift risk to party who can validate
   Mitigate	Add safeguards, monitoring, fallbacks
   Accept	Document and proceed with awareness

   Each mitigation should specify:

   • Actions required
   • Residual risk after mitigation
   • Owner and timeline (if applicable)

4. Assess overall risk profile

   Risk Profile	Criteria
   VERY HIGH	Multiple critical risks, invalidated load-bearing assumptions
   HIGH	Critical risk present, or several high risks
   MODERATE	High risks present but mitigatable
   LOW	No high/critical risks, most assumptions validated
   VERY LOW	All key assumptions validated, minor risks only

5. Generate go/no-go recommendation

   Recommendation	When
   PROCEED	Low/very low risk, assumptions validated
   PROCEED_WITH_CAUTION	Moderate risk, mitigations in place
   SIGNIFICANT_CONCERNS	High risk, key assumptions unvalidated
   DO_NOT_PROCEED	Very high risk, load-bearing assumptions invalid

6. Compile RISK-ASSESSMENT artifact

   Structure per CONTRACT-08:

   • Subject reference and metadata

   • Assessment method (techniques used, assumptions surfaced)

   • Risk list with scores and mitigations

   • Summary with profile and recommendation

   • See:

     templates/risk-assessment-output.md

     for complete template

7. Generate supporting artifacts

   • Assumption Inventory: Complete catalog with validation status

   • Sensitivity Analysis: Impact magnitude per assumption

   • See:

     templates/assumption-inventory-output.md

   • See:

     templates/sensitivity-analysis-output.md

Quality Gates:

• Risks Derived: Assumption-derived risks enumerated
• Go/No-Go Issued: Assessment concludes with recommendation

Output: RISK-ASSESSMENT (CONTRACT-08), Assumption Inventory, Sensitivity Analysis

5. Assumption Taxonomy

Six types of assumptions, ordered by visibility and risk:

5.1 EXPLICIT Assumptions

Definition: Directly stated in the subject document or explicitly acknowledged.

Characteristics:

• Visible in text ("We assume...", "Given that...")
• Author is aware of them
• Often documented in "Assumptions" section

Detection Heuristics:

• Text search for assumption markers
• Review formal "Assumptions" sections
• Check footnotes and caveats

Risk Level: LOW (already acknowledged)

Example:

"This business case assumes 15% year-over-year growth."

5.2 IMPLICIT Assumptions

Definition: Required for conclusions but not stated; inferred from reasoning.

Characteristics:

• Hidden in the logical chain
• Author may not realize they exist
• Often "obvious" to insiders

Detection Heuristics:

• Inversion: "What must be true for this to work?"
• Five Whys: Drill into reasoning
• Outsider test: "What would a newcomer question?"

Risk Level: MEDIUM (can be surfaced with effort)

Example:

Document says "Users will migrate to new system" Implicit: Users have time/motivation to learn new system Implicit: New system is better enough to justify switching cost

5.3 STRUCTURAL Assumptions

Definition: Embedded in how the problem is framed; invisible to those inside the frame.

Characteristics:

• Shape what questions get asked
• Define what's in/out of scope
• Often only visible in hindsight

Detection Heuristics:

• Frame questioning: "Why this frame, not another?"
• Missing voices: "Who isn't represented?"
• Scope boundary probe: "Why is X out of scope?"

Risk Level: HIGH (often invisible until too late)

Example:

Problem framed as "How do we improve our mobile app?" Structural assumption: Mobile app is the right solution Missed: Maybe users want a different channel entirely

5.4 LOAD-BEARING Assumptions

Definition: Assumptions where failure causes the entire plan/decision to collapse.

Characteristics:

• Everything depends on them
• Often single points of failure
• May be any of the other types

Detection Heuristics:

• Dependency mapping: Trace what relies on what
• Pre-mortem: "What caused total failure?"
• Inversion: "Without X, does anything work?"

Risk Level: CRITICAL (single point of failure)

Example:

Strategy depends on "Competitor won't react for 18 months" If wrong: Entire competitive positioning collapses

5.5 CONTEXTUAL Assumptions

Definition: Assumptions about the environment, market, or conditions.

Characteristics:

• External to the organization
• Often based on current state
• May change without warning

Detection Heuristics:

• Environmental scan: Market, regulatory, technology
• Time decay test: "Will this hold in 1/3/5 years?"
• External dependency check

Risk Level: VARIABLE (depends on volatility)

Example:

"Interest rates will remain below 5%" "No new regulations in this space" "Technology X will become standard"

5.6 BEHAVIORAL Assumptions

Definition: Assumptions about how people, teams, or systems will act.

Characteristics:

• Human/organizational behavior
• Often optimistic
• Frequently wrong

Detection Heuristics:

• Stakeholder modeling: "Will they actually do X?"
• Incentive analysis: "Why would they?"
• Historical behavior: "Have they done this before?"

Risk Level: MEDIUM-HIGH (humans are unpredictable)

Example:

"Engineering team will adopt new practices" "Customers will understand the value proposition" "Partners will share data as promised"

6. Surfacing Techniques Summary

See:

references/surfacing-techniques.md

7. Validation Methods Summary

See:

references/validation-methods.md

8. Load-Bearing Analysis Framework

Scoring Dimensions

Priority Calculation

Priority = (Dependency × (1 - Confidence)) / Validation Cost

Interpretation:

• Priority > 3.0: CRITICAL - Validate immediately
• Priority 2.0-3.0: HIGH - Validate before decision
• Priority 1.0-2.0: MEDIUM - Validate if time permits
• Priority < 1.0: LOW - Document and accept

See:

references/load-bearing-analysis.md

9. Output Specifications

9.1 Primary Output: RISK-ASSESSMENT

Compliant with CONTRACT-08 from

artifact-contracts.yaml

<risk_assessment contract="CONTRACT-08">
  <metadata>
    <artifact_id>[unique identifier]</artifact_id>
    <created>[timestamp]</created>
    <subject_reference>[what was assessed]</subject_reference>
    <subject_type>[decision|strategy|plan|architecture|investment|product_direction]</subject_type>
  </metadata>

  <assessment_method>
    <technique>assumption_validation</technique>
    <assumptions_surfaced>[count]</assumptions_surfaced>
    <techniques_applied>[list of surfacing techniques]</techniques_applied>
    <time_horizon>[short_term|medium_term|long_term|all]</time_horizon>
  </assessment_method>

  <risks>
    <risk id="R1">
      <category>[assumption_failure|dependency|behavioral|contextual]</category>
      <description>[risk description]</description>
      <source_assumption>[assumption ID that generated this risk]</source_assumption>
      <trigger>[what would cause this risk to materialize]</trigger>
      <probability>[very_low|low|medium|high|very_high]</probability>
      <impact>[negligible|minor|moderate|major|catastrophic]</impact>
      <risk_score>[calculated score]</risk_score>
      <mitigation>
        <strategy>[avoid|transfer|mitigate|accept]</strategy>
        <actions>
          <action>[specific action]</action>
        </actions>
        <residual_risk>[eliminated|reduced|unchanged]</residual_risk>
      </mitigation>
    </risk>
    <!-- Additional risks -->
  </risks>

  <summary>
    <total_risks>[count]</total_risks>
    <risk_profile>[very_high|high|moderate|low|very_low]</risk_profile>
    <top_risks>
      <ref risk_id="R1"/>
      <ref risk_id="R2"/>
      <ref risk_id="R3"/>
    </top_risks>
    <go_no_go_assessment>[proceed|proceed_with_caution|significant_concerns|do_not_proceed]</go_no_go_assessment>
    <key_assumptions>
      <assumption id="A1" confidence="[value]" status="[status]">[statement]</assumption>
    </key_assumptions>
    <recommendation>[narrative recommendation]</recommendation>
  </summary>
</risk_assessment>

See:

templates/risk-assessment-output.md

9.2 Secondary Output: Assumption Inventory

<assumption_inventory>
  <metadata>
    <subject_reference>[what was analyzed]</subject_reference>
    <total_assumptions>[count]</total_assumptions>
    <validation_coverage>[percentage validated]</validation_coverage>
  </metadata>

  <assumptions>
    <assumption id="A1">
      <type>[EXPLICIT|IMPLICIT|STRUCTURAL|LOAD-BEARING|CONTEXTUAL|BEHAVIORAL]</type>
      <statement>[clear, falsifiable statement]</statement>
      <source>[how it was identified]</source>
      <confidence>[0.0-1.0]</confidence>
      <epistemic_label>[VERIFIED|LIKELY|POSSIBLE|SPECULATIVE|UNKNOWN]</epistemic_label>
      <load_bearing_score>[priority score]</load_bearing_score>
      <validation_status>[VALIDATED|PARTIAL|UNVALIDATED|INVALIDATED|CONTESTED]</validation_status>
      <validation_method>[methods used]</validation_method>
      <dependencies>
        <ref>[what depends on this]</ref>
      </dependencies>
      <invalidation_triggers>
        <trigger>[what would make this false]</trigger>
      </invalidation_triggers>
    </assumption>
    <!-- Additional assumptions -->
  </assumptions>
</assumption_inventory>

See:

templates/assumption-inventory-output.md

9.3 Secondary Output: Sensitivity Analysis

<sensitivity_analysis>
  <metadata>
    <subject_reference>[what was analyzed]</subject_reference>
    <assumptions_analyzed>[count]</assumptions_analyzed>
  </metadata>

  <scenarios>
    <scenario assumption_id="A1">
      <what_if>[Assumption A1 is FALSE]</what_if>
      <immediate_impacts>
        <impact>[description]</impact>
      </immediate_impacts>
      <cascade_effects>
        <effect>[description]</effect>
      </cascade_effects>
      <decision_change>[would decision change? how?]</decision_change>
      <impact_magnitude>[negligible|minor|moderate|major|catastrophic]</impact_magnitude>
    </scenario>
    <!-- Additional scenarios -->
  </scenarios>

  <summary>
    <decision_robustness_score>[0-100]</decision_robustness_score>
    <most_sensitive_assumptions>
      <ref assumption_id="A3"/>
      <ref assumption_id="A7"/>
    </most_sensitive_assumptions>
    <robustness_assessment>[narrative]</robustness_assessment>
  </summary>
</sensitivity_analysis>

See:

templates/sensitivity-analysis-output.md

10. Quality Gates

Gate Requirements by Intensity

11. Workflow Integration

Upstream Skills

research-interviewer

expert-panel-deliberation

create-research-brief

Downstream Skills

expert-panel-deliberation

generate-ideas

Skill Chaining Example

research-interviewer      → KNOWLEDGE-CORPUS
                               ↓
assumption-validator      → RISK-ASSESSMENT
                               ↓
expert-panel-deliberation → Validated risk mitigation plan

12. Behavioral Guidelines

Approach Principles

• Curious, not adversarial: Surface assumptions to understand, not to attack
• Humble about certainty: Calibrate confidence honestly; overconfidence is dangerous
• Specific, not vague: Each assumption should be falsifiable
• Proportionate effort: Match validation depth to decision stakes
• Actionable output: Every finding should inform a decision or action
• Transparent reasoning: Show how assumptions connect to risks
• Constructive framing: Present findings to enable better decisions, not to criticize

Tone Calibration by Intensity

Communication Guidelines

• State assumptions as falsifiable propositions, not vague concerns
• Distinguish between "unvalidated" (unknown) and "invalidated" (known false)
• When confidence is low, say so explicitly
• Provide evidence for validation claims
• Recommend specific actions, not just flag risks

13. References

references/assumption-taxonomy.md

references/surfacing-techniques.md

references/validation-methods.md

references/load-bearing-analysis.md

references/what-if-framework.md

references/confidence-calibration.md

Core Library References

core/skill-patterns.yaml

core/artifact-contracts.yaml

core/scoring-rubrics.yaml

core/scoring-rubrics.yaml

core/technique-taxonomy.yaml

14. Templates

templates/risk-assessment-output.md

templates/assumption-inventory-output.md

templates/sensitivity-analysis-output.md

15. Examples

Example 1: Decision Validation — Microservices Migration

input:
  subject: "Decision to migrate from monolith to microservices architecture"
  subject_type: architecture
  validation_intensity: rigorous
  assumption_depth: full_structural
  counterfactual_analysis: true
  time_horizon: long_term

flow:
  phase_1:
    framing: "Validate assumptions in architecture migration decision"
    scope: "Technical, organizational, and timeline assumptions"
    stakeholders: ["CTO", "Engineering leads", "Platform team"]

  phase_2:
    explicit_assumptions:
      - A1: "Current monolith cannot scale beyond 10K concurrent users"
      - A2: "Migration can be completed in 18 months"
      - A3: "Team has sufficient microservices expertise"
    implicit_assumptions:
      - A4: "Service boundaries are well-understood"
      - A5: "Operational complexity increase is manageable"
      - A6: "Data consistency requirements can be met with eventual consistency"
      - A7: "Deployment pipeline can be upgraded in parallel"
    structural_assumptions:
      - A8: "Microservices is the right architectural pattern for our needs"
      - A9: "We've correctly identified the performance bottleneck"
    total: 9 assumptions surfaced

  phase_3:
    classification:
      - A1: CONTEXTUAL, LOAD-BEARING (everything depends on this being true)
      - A2: BEHAVIORAL (team velocity assumption)
      - A3: BEHAVIORAL, LOAD-BEARING (critical capability)
      - A8: STRUCTURAL (framing assumption)
    load_bearing_analysis:
      - A1: Dependency=5, Reversibility=2, ValidationCost=2, Confidence=0.6 → Priority=4.0
      - A3: Dependency=5, Reversibility=3, ValidationCost=3, Confidence=0.4 → Priority=4.0
      - A8: Dependency=5, Reversibility=1, ValidationCost=4, Confidence=0.5 → Priority=3.1
    top_5: [A1, A3, A8, A2, A5]

  phase_4:
    validation_results:
      - A1: PARTIAL (load tests show 8K limit, but unclear if that's the monolith's fault)
           Confidence: 0.65, POSSIBLE
      - A3: UNVALIDATED (team has 1 person with production microservices experience)
           Confidence: 0.35, SPECULATIVE
      - A8: PARTIAL (alternatives like modular monolith not fully evaluated)
           Confidence: 0.55, POSSIBLE
    counterfactuals:
      - A3_FALSE: "Team lacks expertise"
        Impact: MAJOR (delays, quality issues, operational incidents)
        Decision change: Would need to hire or postpone
      - A8_FALSE: "Microservices isn't the right pattern"
        Impact: CATASTROPHIC (complete rework, wasted 18 months)
        Decision change: Would choose different architecture

  phase_5:
    risks_derived:
      - R1: "Team capability gap causes delivery failure" (from A3)
           Probability: high, Impact: major, Score: 3.4
      - R2: "Performance bottleneck not actually in monolith" (from A1, A9)
           Probability: medium, Impact: major, Score: 2.8
      - R3: "Microservices complexity exceeds operational capacity" (from A5)
           Probability: medium, Impact: moderate, Score: 2.1
    risk_profile: HIGH
    go_no_go: SIGNIFICANT_CONCERNS

output:
  risk_assessment:
    total_risks: 7
    critical_risks: 0
    high_risks: 2
    profile: HIGH
    recommendation: "SIGNIFICANT_CONCERNS - Do not proceed without addressing team
                     capability gap (A3). Consider hiring 2+ experienced engineers
                     or engaging architecture consultancy. Also evaluate modular
                     monolith alternative before committing to microservices (A8)."
  key_findings:
    - "Load-bearing assumption A3 (team expertise) is SPECULATIVE (confidence 0.35)"
    - "Structural assumption A8 (microservices is right) was not rigorously evaluated"
    - "If A3 is wrong, expect 6-12 month delays and quality issues"

Example 2: Strategy Validation — European Market Entry

input:
  subject: "Strategy to enter European market in Q3"
  subject_type: strategy
  validation_intensity: standard
  assumption_depth: include_implicit
  counterfactual_analysis: true
  time_horizon: medium_term

flow:
  phase_1:
    framing: "Validate assumptions in EU market entry strategy"
    scope: "Market, regulatory, operational, competitive assumptions"
    stakeholders: ["CEO", "VP Sales", "Legal", "Finance"]

  phase_2:
    explicit_assumptions:
      - A1: "EU market opportunity is $50M annually"
      - A2: "GDPR compliance achievable by Q2"
      - A3: "Can hire local sales team within 3 months"
    implicit_assumptions:
      - A4: "Brand will translate to EU market"
      - A5: "Pricing model works in EU (different from US)"
      - A6: "No significant competitive response for 6 months"
      - A7: "Payment infrastructure compatible with EU systems"
    total: 7 assumptions surfaced

  phase_3:
    load_bearing_analysis:
      - A2: Dependency=5, ValidationCost=3, Confidence=0.4 → Priority=3.0 (LOAD-BEARING)
      - A6: Dependency=4, ValidationCost=4, Confidence=0.3 → Priority=2.1
      - A4: Dependency=4, ValidationCost=3, Confidence=0.5 → Priority=1.3
    top_5: [A2, A6, A1, A4, A5]

  phase_4:
    validation_results:
      - A2: PARTIAL - Legal says 6 months minimum, not 3 months
           Confidence: 0.50, POSSIBLE
      - A6: UNVALIDATED - No competitive intelligence conducted
           Confidence: 0.30, SPECULATIVE
      - A1: PARTIAL - $50M based on industry reports, not validated for our segment
           Confidence: 0.55, POSSIBLE
    counterfactuals:
      - A2_FALSE: "GDPR compliance takes 6+ months"
        Impact: MODERATE (Q3 launch becomes Q4 or later)
      - A6_FALSE: "Competitor responds immediately"
        Impact: MAJOR (first-mover advantage lost, pricing pressure)

  phase_5:
    risks_derived:
      - R1: "GDPR timeline slip delays launch" (from A2)
      - R2: "Competitive response erodes market opportunity" (from A6)
      - R3: "Market opportunity overestimated" (from A1)
    risk_profile: MODERATE
    go_no_go: PROCEED_WITH_CAUTION

output:
  risk_assessment:
    profile: MODERATE
    recommendation: "PROCEED_WITH_CAUTION - Adjust timeline to Q4 to allow GDPR buffer.
                     Conduct competitive intelligence before launch. Validate market
                     size with primary research in target segments."

Example 3: Architecture Choice — Event Sourcing

input:
  subject: "Use event sourcing for transaction processing system"
  subject_type: architecture
  validation_intensity: standard
  assumption_depth: include_implicit
  counterfactual_analysis: true
  time_horizon: long_term

flow:
  phase_1:
    framing: "Validate assumptions in event sourcing architecture choice"
    scope: "Technical capabilities, team skills, operational requirements"

  phase_2:
    explicit_assumptions:
      - A1: "Full audit trail is a regulatory requirement"
      - A2: "Query patterns are primarily temporal (time-series)"
      - A3: "Event schema will remain stable"
    implicit_assumptions:
      - A4: "Team can learn event sourcing patterns effectively"
      - A5: "Eventual consistency acceptable for all use cases"
      - A6: "Read model rebuild time acceptable in failure scenarios"
    total: 6 assumptions surfaced

  phase_3:
    load_bearing_analysis:
      - A1: Dependency=5, Confidence=0.9 → Priority=0.6 (VALIDATED)
      - A5: Dependency=4, Confidence=0.5 → Priority=2.0
      - A4: Dependency=3, Confidence=0.6 → Priority=1.2
    top_5: [A5, A6, A4, A2, A3]

  phase_4:
    validation_results:
      - A1: VALIDATED - Regulatory docs confirm audit requirement
           Confidence: 0.95, VERIFIED
      - A5: PARTIAL - Finance team needs strong consistency for reconciliation
           Confidence: 0.60, POSSIBLE
      - A4: LIKELY - Team has completed event sourcing training
           Confidence: 0.75, LIKELY
    counterfactuals:
      - A5_FALSE: "Some use cases need strong consistency"
        Impact: MODERATE (need CQRS pattern, adds complexity)

  phase_5:
    risk_profile: LOW
    go_no_go: PROCEED

output:
  risk_assessment:
    profile: LOW
    recommendation: "PROCEED - Core requirement (A1) validated. Implement CQRS pattern
                     to handle strong consistency requirements for finance (A5).
                     Continue team training program."

16. Quick Start

Minimal Invocation

Validate assumptions in: [paste decision/strategy/plan]

Standard Invocation

subject_type: decision
validation_intensity: standard
assumption_depth: include_implicit

Subject: [description or document]

Full Parameter Invocation

subject_type: strategy
validation_intensity: rigorous
assumption_depth: full_structural
counterfactual_analysis: true
confidence_threshold: 0.8
time_horizon: long_term

Subject: [detailed description or document reference]

Additional context:
- Stakeholders: [who should be consulted]
- Time constraint: [when is decision needed]
- Protected assumptions: [any executive mandates]