aura-labs.ai

AURA Reputation Specification v1.0

Document Status: Draft for Review
Version: 1.0
Date: November 10, 2025
Owner: AURA Labs Architecture Team
Classification: Internal - Strategic

Executive Summary

This specification defines AURA’s multi-dimensional reputation system, a core component enabling cooperative, values-aligned commerce between Scout (buyer) and Beacon (seller) agents. Unlike traditional e-commerce reputation systems that reduce trust to single-dimensional ratings, AURA’s reputation architecture captures behavioral patterns across multiple dimensions, enabling sophisticated matching, network health maintenance, and incentive alignment.

Key Design Principles:

Strategic Rationale:
The reputation system operationalizes our thesis that agents optimizing for cooperative, values-aligned outcomes will outperform purely transactional, rational optimization. By measuring and rewarding “nice” behavior (responsiveness, transparency, fairness, consistency), we create network effects that attract high-quality participants and deter opportunistic actors.

1. System Overview

1.1 Architectural Context

The reputation system resides within AURA Core’s Client Integration & Management domain and interacts with:

1.2 Reputation Philosophy

AURA’s reputation system is built on insights from behavioral economics (bounded rationality, trust formation), game theory (repeated games, folk theorem), and market design (matching stability, mechanism design):

From Behavioral Economics:

From Game Theory:

From Market Design:

1.3 Data Architecture

Reputation data is stored in AURA Core’s distributed ledger with immutable transaction history and versioned reputation scores. Each agent maintains:

2. Scout Reputation Specifications

Scout agents represent buyer interests. Their reputation reflects reliability, engagement quality, and values consistency as commerce participants.

2.1 Scout Reputation Dimensions

Dimension Description Range Weight
Engagement Integrity (EI) Consistency between stated intent and actual behavior 0-100 0.25
Transaction Reliability (TR) Completion rate and payment reliability 0-100 0.30
Profile Consistency (PC) Alignment between declared preferences and actual choices 0-100 0.20
Network Contribution (NC) Feedback quality, dispute fairness, ecosystem participation 0-100 0.15
Values Authenticity (VA) Consistency between stated values and purchasing decisions 0-100 0.10

Total Scout Reputation Score:

SR = (0.25 × EI) + (0.30 × TR) + (0.20 × PC) + (0.15 × NC) + (0.10 × VA)

2.2 Engagement Integrity (EI)

Measures whether Scout follows through on declared shopping intent.

Calculation:

EI = 100 × (Completed_Engagements / Initiated_Engagements) × Recency_Weight

Components:

Scoring Thresholds:

Penalty Events:

2.3 Transaction Reliability (TR)

Measures completion rate and payment dependability.

Calculation:

TR = (0.5 × Completion_Rate + 0.3 × Payment_Timeliness + 0.2 × Cancellation_Avoidance) × 100

Components:

Completion_Rate:

Completion_Rate = Completed_Transactions / Accepted_Offers

Payment_Timeliness:

Payment_Timeliness = Σ(min(1, Expected_Time / Actual_Time)) / Total_Transactions

Cancellation_Avoidance:

Cancellation_Avoidance = 1 - (Scout_Cancellations / Total_Accepted_Offers)

Scoring Thresholds:

Penalty Events:

2.4 Profile Consistency (PC)

Measures alignment between declared preferences and actual behavior.

Calculation:

PC = 100 × (1 - Divergence_Score) × Temporal_Stability

Divergence_Score:

Divergence_Score = Σ(|Profile_Weight_i - Behavioral_Weight_i|) / N_dimensions
where Profile_Weight_i = declared importance of attribute i (e.g., sustainability: 0.8)
      Behavioral_Weight_i = inferred importance from actual choices
      N_dimensions = number of tracked preference dimensions

Behavioral Weight Inference: For each preference dimension, calculate revealed preference through choice analysis:

Behavioral_Weight_i = Σ(Choice_Score_i × Transaction_Value) / Σ(Transaction_Value)
where Choice_Score_i = normalized attribute value of purchased item on dimension i

Example:

Temporal_Stability:

Temporal_Stability = 1 - (Profile_Changes / Months_Active)
where Profile_Changes = number of significant preference updates
      Significant = change of ≥0.2 in any dimension weight

Scoring Thresholds:

2.5 Network Contribution (NC)

Measures quality of ecosystem participation.

Calculation:

NC = (0.4 × Feedback_Quality + 0.3 × Dispute_Fairness + 0.3 × Community_Value) × 100

Feedback_Quality:

Feedback_Quality = (Detailed_Reviews / Total_Reviews) × Helpfulness_Score
where Helpfulness_Score = Beacon_Helpfulness_Ratings / Reviews_Rated

Dispute_Fairness:

Dispute_Fairness = 1 - (Unfounded_Disputes / Total_Disputes)
where Unfounded = disputes resolved in Beacon's favor

Community_Value:

Community_Value = (Profile_Completeness + Referral_Quality + Response_Rate) / 3

Scoring Thresholds:

2.6 Values Authenticity (VA)

Measures consistency between stated values and purchasing decisions.

Calculation:

VA = 100 × Correlation(Stated_Values, Purchase_Values)

Methodology:

  1. Extract Stated Values: Scout profile declares importance of values dimensions:
    • Sustainability (environmental impact)
    • Ethics (labor practices, supply chain)
    • Social Impact (community benefit, social good)
    • Local Support (small business, local economy)
    • Innovation (cutting-edge, new technology)
  2. Measure Purchase Values: Analyze attributes of purchased products:
    • Product sustainability ratings (if available)
    • Seller certifications (B-Corp, Fair Trade, etc.)
    • Social impact indicators
    • Business size and locality
    • Product innovation scores
  3. Calculate Correlation: 
    For each values dimension v:
  Stated_Importance_v = profile declared weight (0-1)
  Purchase_Alignment_v = avg value score of purchases on dimension v (0-1)
   
VA = 100 × [1 - (Σ|Stated_v - Purchase_v| / N_values_dimensions)]

Scoring Thresholds:

Special Considerations:

3. Beacon Reputation Specifications

Beacon agents represent seller interests. Their reputation reflects service quality, transparency, fairness, and ecosystem contribution.

3.1 Beacon Reputation Dimensions

Dimension Description Range Weight
Offer Quality (OQ) Relevance, competitiveness, and honesty of offers 0-100 0.25
Transaction Excellence (TE) Fulfillment reliability and service quality 0-100 0.30
Transparency Score (TS) Clarity of terms, accurate product representation 0-100 0.20
Fairness Metric (FM) Equitable treatment across Scout segments 0-100 0.15
Network Stewardship (NS) Contribution to ecosystem health 0-100 0.10

Total Beacon Reputation Score:

BR = (0.25 × OQ) + (0.30 × TE) + (0.20 × TS) + (0.15 × FM) + (0.10 × NS)

3.2 Offer Quality (OQ)

Measures relevance, competitiveness, and honesty of offers made to Scouts.

Calculation:

OQ = (0.4 × Relevance_Score + 0.35 × Competitiveness + 0.25 × Offer_Integrity) × 100

Relevance_Score:

Relevance_Score = Scout_Acceptance_Rate × Match_Precision
where Scout_Acceptance_Rate = Offers_Accepted / Offers_Made
      Match_Precision = Avg(Scout_Constraint_Satisfaction_per_Offer)

Competitiveness:

Competitiveness = Percentile_Rank(Offer_Value_vs_Market)
where Offer_Value = (Product_Quality_Score / Price) normalized by category
      Market = comparable offers from other Beacons for similar products

Offer_Integrity:

Offer_Integrity = 1 - [(Hidden_Costs + Bait_and_Switch + Misleading_Terms) / Total_Offers]

Scoring Thresholds:

Penalty Events:

3.3 Transaction Excellence (TE)

Measures fulfillment reliability and post-transaction service quality.

Calculation:

TE = (0.4 × Fulfillment_Score + 0.35 × Service_Quality + 0.25 × Issue_Resolution) × 100

Fulfillment_Score:

Fulfillment_Score = (On_Time_Delivery + Product_Match + Condition_Quality) / 3

Service_Quality:

Service_Quality = (Avg_Scout_Service_Rating + Communication_Responsiveness) / 2

Issue_Resolution:

Issue_Resolution = (Issues_Resolved_Favorably / Total_Issues) × Resolution_Speed
where Resolution_Speed = Avg(max(0, 1 - (Resolution_Days / 14)))

Scoring Thresholds:

Penalty Events:

3.4 Transparency Score (TS)

Measures clarity and honesty in product representation and terms.

Calculation:

TS = (0.5 × Description_Accuracy + 0.3 × Terms_Clarity + 0.2 × Disclosure_Completeness) × 100

Description_Accuracy:

Description_Accuracy = 1 - (Mismatch_Reports / Total_Transactions)
where Mismatch_Reports = Scout reports of product not matching description

Terms_Clarity:

Terms_Clarity = (1 - Clarification_Requests / Total_Offers) × Scout_Comprehension_Rating
where Clarification_Requests = Scout requests for term explanation before acceptance
      Scout_Comprehension_Rating = post-transaction survey: "Terms were clear" (1-5)

Disclosure_Completeness:

Disclosure_Completeness = Checklist_Completion_Rate × Proactive_Disclosure_Score

Scoring Thresholds:

Penalty Events:

3.5 Fairness Metric (FM)

Measures equitable treatment across Scout segments.

Calculation:

FM = 100 × (1 - Price_Discrimination_Score) × Service_Equality_Score

Price_Discrimination_Score:

Price_Discrimination_Score = Variance(Price_Offered / Market_Price) across Scout_Segments
where Scout_Segments = groups by demographics, purchase history, reputation tier

Service_Equality_Score:

Service_Equality_Score = 1 - |Fulfillment_Time_Variance| across Scout_Reputation_Tiers

Algorithmic Auditing: AURA Core conducts quarterly algorithmic fairness audits:

  1. Segment Scouts by reputation quintile and demographic attributes
  2. Analyze offer acceptance rates, pricing, fulfillment times, issue resolution
  3. Flag Beacons with statistically significant (p < 0.05) disparate treatment
  4. Trigger investigation if FM < 60 persists for 30+ days

Scoring Thresholds:

Penalty Events:

3.6 Network Stewardship (NS)

Measures contribution to ecosystem health and long-term sustainability.

Calculation:

NS = (0.35 × Protocol_Compliance + 0.30 × Data_Quality + 0.20 × Innovation_Participation + 0.15 × Community_Support) × 100

Protocol_Compliance:

Protocol_Compliance = (API_Reliability + Standards_Adherence + Update_Timeliness) / 3

Data_Quality:

Data_Quality = (Catalog_Completeness + Inventory_Accuracy + Metadata_Richness) / 3

Innovation_Participation:

Community_Support:

Community_Support = (Response_to_Platform_Inquiries + Marketplace_Advocacy + Scout_Education) / 3

Scoring Thresholds:

4. Scoring Algorithms

4.1 Reputation Update Frequency

Real-Time Updates (Immediate):

Daily Batch Updates (00:00 UTC):

Weekly Batch Updates (Sunday 00:00 UTC):

Monthly Audit (1st of month):

4.2 New Agent Initialization

Scout Initial Reputation:

New Scout starts with baseline:
  EI = 75 (neutral, no history)
  TR = 80 (benefit of doubt on payment reliability)
  PC = 70 (no behavioral data yet)
  NC = 60 (minimal participation expected initially)
  VA = N/A (informational only until 10 transactions)
  
Initial SR = (0.25 × 75) + (0.30 × 80) + (0.20 × 70) + (0.15 × 60) + (0.10 × 70)
           = 18.75 + 24 + 14 + 9 + 7
           = 72.75 (Adequate starting point)

Beacon Initial Reputation:

New Beacon starts with baseline:
  OQ = 70 (neutral, will learn Scout preferences)
  TE = 75 (assumed competent until proven otherwise)
  TS = 80 (benefit of doubt on transparency)
  FM = 90 (assume fairness until evidence suggests otherwise)
  NS = 65 (basic protocol compliance)
  
Initial BR = (0.25 × 70) + (0.30 × 75) + (0.20 × 80) + (0.15 × 90) + (0.10 × 65)
           = 17.5 + 22.5 + 16 + 13.5 + 6.5
           = 76 (Solid starting point)

Probationary Period:

4.3 Reputation Decay

Reputation must be maintained through continued participation.

Inactivity Decay (Scout):

If Days_Since_Last_Transaction > 180:
  SR_decay = SR × (0.99)^((Days - 180) / 30)
  
Example: Scout inactive for 360 days (180 + 180)
  Decay periods = 180 / 30 = 6
  SR_new = SR_old × (0.99)^6 = SR_old × 0.941
  
A 90 SR drops to 84.7 after 1 year inactivity

Inactivity Decay (Beacon):

If Days_Since_Last_Transaction > 90:
  BR_decay = BR × (0.98)^((Days - 90) / 30)
  
Beacons decay faster (0.98 vs 0.99) due to seller role expectations
Example: 360 days inactive
  Decay periods = 270 / 30 = 9
  BR_new = BR_old × (0.98)^9 = BR_old × 0.834
  
A 90 BR drops to 75 after 1 year inactivity

Reactivation:

4.4 Reputation Recovery Mechanisms

Agents can recover from reputation damage through consistent positive behavior.

Rehabilitation Bonus:

If agent maintains positive trajectory for consecutive_periods:
  Bonus = min(5, consecutive_periods × 0.5) per period
  where consecutive_periods = weeks with net positive reputation change
  
Example: Beacon with BR = 55 improves consistently for 8 weeks
  Week 1-4: +0.5 bonus each = +2 points
  Week 5-8: +2.5 bonus each = +10 points (capped at +5 per week)
  Total potential recovery: +30 points over 8 weeks

Good Samaritan Bonus (Network Contribution): Exceptional ecosystem contributions accelerate recovery:

Reputation Floor:

4.5 Reputation Tiers and Privileges

Reputation unlocks access tiers with differentiated experience.

Scout Tiers:

Tier SR Range Benefits
Platinum 90-100 Priority Beacon attention, early access to new features, premium support, exclusive offers from top Beacons
Gold 75-89 Standard access, eligible for time-sensitive deals, responsive support
Silver 60-74 Standard access, normal priority
Bronze 40-59 Standard access, limited time-sensitive offers
Probation 20-39 Restricted access, additional verification required, limited Beacon exposure

Beacon Tiers:

Tier BR Range Benefits
Elite 90-100 Featured placement, priority Scout exposure, co-marketing opportunities, reduced platform fees (5% discount)
Premier 75-89 Standard placement, full Scout access, standard platform fees
Standard 60-74 Standard placement, full Scout access
Developing 40-59 Standard placement, potential increased oversight
Restricted 20-39 Limited Scout exposure, mandatory monitoring, potential suspension review

Tier Movement:

5. Profile Compatibility Integration

Reputation scores interact with profile matching to optimize Scout-Beacon connections.

5.1 Compatibility-Weighted Reputation

When AURA’s Market Navigation Engine surfaces Beacon offers to a Scout, it calculates Compatibility-Weighted Reputation (CWR):

CWR = (Base_Reputation × 0.6) + (Compatibility_Score × 0.4)
where Compatibility_Score = Profile_Alignment × Values_Alignment

Profile_Alignment:

Profile_Alignment = 100 × (1 - Σ|Scout_Preference_i - Beacon_Capability_i| / N)

Values_Alignment:

Values_Alignment = 100 × Σ(Scout_Value_i × Beacon_Value_i) / sqrt(Σ(Scout_Value_i²) × Σ(Beacon_Value_i²))

Practical Example:

Scout seeks sustainable outdoor gear, values environment = 0.9, price = 0.5
Beacon A: BR = 85, strong sustainability (0.9), moderate price (0.6)
Beacon B: BR = 92, weak sustainability (0.4), best price (0.9)

Beacon A:
  Profile_Alignment = 100 × (1 - (|0.9-0.9| + |0.5-0.6|)/2) = 95
  Values_Alignment = high (sustainability match)
  Compatibility_Score ≈ 92
  CWR = (85 × 0.6) + (92 × 0.4) = 51 + 36.8 = 87.8

Beacon B:
  Profile_Alignment = 100 × (1 - (|0.9-0.4| + |0.5-0.9|)/2) = 55
  Values_Alignment = low (sustainability mismatch)
  Compatibility_Score ≈ 50
  CWR = (92 × 0.6) + (50 × 0.4) = 55.2 + 20 = 75.2

Result: Beacon A ranked higher despite lower base reputation due to superior compatibility

5.2 Compatibility Feedback Loop

Agent behavior updates compatibility assessments over time.

Scout Profile Refinement: After each transaction, AURA updates Scout’s implied preferences:

Updated_Preference_i = (0.7 × Stated_Preference_i) + (0.3 × Revealed_Preference_i)
where Revealed_Preference_i = normalized attribute value of chosen product

Beacon Specialization Identification: AURA identifies Beacon specializations through transaction patterns:

Beacon_Specialization_Score_segment = Success_Rate_segment / Avg_Success_Rate_all
where segment = Scout demographic, preference cluster, or values orientation

5.3 Cold Start Problem Mitigation

New agents lack behavioral history for accurate compatibility assessment.

Scout Cold Start:

  1. Onboarding Survey: Detailed preference elicitation (20-30 questions)
  2. Proxy Data: If authorized, import past purchase history from integrated platforms
  3. Collaborative Filtering: “Scouts like you tend to prefer…”
  4. Progressive Disclosure: Show diverse options initially, narrow based on early interactions

Beacon Cold Start:

  1. Seller Interview: Detailed product catalog and values assessment during onboarding
  2. Category Benchmarks: Compare to similar sellers in category
  3. Test Offers: Initial offers to diverse Scout segments to learn strengths
  4. Mentor Program: Pair with established Beacon for guidance

6. Network Health Metrics and Interventions

AURA Core monitors system-wide reputation distributions to maintain ecosystem health.

6.1 Population Health Indicators

Scout Population Health:

SPH = (0.4 × Avg_SR) + (0.3 × Engagement_Rate) + (0.2 × Retention_Rate) + (0.1 × Growth_Rate)

Beacon Population Health:

BPH = (0.4 × Avg_BR) + (0.3 × Seller_Satisfaction) + (0.2 × Transaction_Volume_Growth) + (0.1 × New_Beacon_Activation)

6.2 Early Warning System

AURA Core monitors reputation trends for concerning patterns:

Reputation Inflation Detection:

If Avg_SR or Avg_BR increases by >5 points in 30 days without corresponding quality improvement:
  → Trigger scoring algorithm audit
  → Check for gaming behaviors
  → Adjust scoring weights if needed

Reputation Polarization Detection:

If Reputation_Distribution_Variance > Threshold:
  → Indicates clustering into "very good" and "very bad" agents
  → May signal need for rehabilitation programs
  → Could indicate insufficient differentiation in middle tiers

Reputation Deflation Detection:

If Avg_SR or Avg_BR decreases by >3 points in 30 days:
  → Investigate whether scoring is too harsh
  → Check for platform-wide technical issues affecting scores
  → Consider temporary scoring relief measures

6.3 Intervention Mechanisms

Tier-Specific Interventions:

For Low-Reputation Scouts (SR < 40):

  1. Educational Outreach: Send personalized guidance on improving reputation
  2. Onboarding Review: Offer to re-onboard with platform best practices
  3. Targeted Support: Assign customer success manager for coaching
  4. Rehabilitation Program: Structured 60-day improvement plan with milestones

For Low-Reputation Beacons (BR < 40):

  1. Performance Review: Deep dive into reputation drivers with seller
  2. Best Practice Guidance: Share strategies from high-performing Beacons
  3. Operational Audit: Identify process improvements (fulfillment, communication, transparency)
  4. Probationary Period: 90 days to demonstrate improvement or face suspension
  5. Suspension: If BR < 30 for 60+ consecutive days, temporary platform removal

For Reputation Gaming:

If suspicious patterns detected (e.g., collusive rating, fake transactions):
  1. Flag account for investigation
  2. Freeze reputation at current level
  3. Manual review of transaction history
  4. If confirmed: Reputation penalty (-20 to -50 points) + warning
  5. If repeated: Permanent account suspension

6.4 Systemic Health Corrections

Category Rebalancing: If specific product categories show systematically lower Beacon reputations:

Seasonal Adjustments: Major shopping seasons (holidays, back-to-school) can strain Beacon capabilities:

Market Correction Mechanisms: If >20% of Beacons fall below BR < 60 for 60+ days:

7. Incentive Mechanisms

Reputation directly influences economic outcomes, creating incentive alignment.

7.1 Scout Incentives

Direct Benefits:

For SR ≥ 90 (Platinum tier):
  - Access to exclusive deals (avg 10-15% additional savings)
  - Priority customer support (target response time: <1 hour vs <24 hours standard)
  - Early access to new platform features (beta invitations)
  - Featured Scout badge (signals reliability to Beacons for negotiated pricing)

Indirect Benefits:

High SR → Better Beacon Response:
  - Beacons prioritize high-reputation Scouts for limited inventory
  - More likely to offer personalized deals
  - More favorable negotiation outcomes
  
High SR → Improved Matching:
  - AURA algorithm surfaces better-fit Beacons
  - Reduces time-to-purchase
  - Higher satisfaction with recommendations

Behavioral Nudges:

Reputation Recovery Path:
  "You're 3 completed transactions away from Gold tier benefits!"
  "Maintaining your current pace, you'll reach Platinum in 45 days"
  
Reputation Risk Warnings:
  "Abandoning this negotiation may affect your Engagement Integrity score"
  "Your Transaction Reliability is excellent - keep it up!"

7.2 Beacon Incentives

Economic Incentives:

Platform Fee Structure (example):
  BR 90-100 (Elite):     5% platform fee (5% discount from standard)
  BR 75-89 (Premier):    5.25% platform fee (0.25% discount)
  BR 60-74 (Standard):   5.5% platform fee (standard rate)
  BR 40-59 (Developing): 6% platform fee (+0.5% premium)
  BR 20-39 (Restricted): 7% platform fee (+1.5% premium)
  
Annual savings for Elite Beacon with $1M GMV:
  5% vs 5.5% = $5,000 annual savings

Visibility Incentives:

Algorithm Placement Boost:
  Elite Beacons (BR ≥ 90): 2.0× baseline exposure in search results
  Premier Beacons (BR 75-89): 1.5× baseline exposure
  Standard Beacons (BR 60-74): 1.0× baseline (standard)
  Developing Beacons (BR 40-59): 0.7× baseline
  Restricted Beacons (BR < 40): 0.4× baseline
  
Impact: Elite Beacon with BR = 95 gets 2× visibility vs Standard Beacon (BR = 65)
→ Potential 50-100% increase in Scout engagement

Quality Signal:

Elite Badge Display:
  - Beacons with BR ≥ 90 earn "AURA Elite Seller" badge
  - Displayed prominently in Scout interfaces
  - Increases conversion rate by est. 15-25%
  - Competitive advantage in crowded categories

Reputational Equity:

High reputation becomes valuable intangible asset:
  - Attracts high-value Scouts
  - Commands premium pricing authority
  - Enables differentiation from competitors
  - Builds long-term Scout relationships
  
Loss aversion motivates maintenance:
  - BR accumulated over years of effort
  - Drop from Elite (BR 92) to Premier (BR 88) = visible loss of status
  - Incentivizes consistent excellence

7.3 Preventing Gaming

Multi-dimensional Resistance:

Temporal Consistency Required:

Cross-Validation:

Behavioral Red Flags:

Automated Detection of Gaming:
  - Sudden reputation spikes (>10 points in 7 days) → Manual review
  - Pattern of transactions with same Scout/Beacon repeatedly → Collusion check
  - Reputation volatility inconsistent with transaction volume → Suspicious
  - Review text patterns suggesting fake feedback (NLP analysis)

Penalty for Gaming:

If gaming detected and confirmed:
  - Immediate reputation reset to minimum (SR/BR = 20)
  - 90-day probation with enhanced monitoring
  - Permanent flag in agent record (visible to AURA, not public)
  - Repeat offense: Permanent ban from platform

8. Governance and Appeals Process

Reputation affects livelihoods. Fair governance and appeals are essential.

8.1 Dispute Resolution Framework

Step 1: Automated Mediation

When Scout or Beacon disputes reputation impact:
  1. AURA Core presents evidence for reputation change
  2. Agent submits counter-evidence
  3. Automated system checks for:
     - Data entry errors
     - Duplicate penalty applications
     - Scoring algorithm bugs
  4. If resolvable: Automatic correction applied
  5. If not: Escalate to Step 2

Step 2: Human Review

AURA Trust & Safety Team:
  - Reviews full transaction history
  - Interviews Scout and Beacon separately
  - Examines system logs and reputation calculation details
  - Applies "reasonable person" standard for conduct evaluation
  - Issues binding decision within 14 business days

Step 3: Independent Arbitration

If agent disputes Human Review decision:
  - Can request independent arbitration (requires fee: $100-$500 based on impact)
  - Third-party arbitrator selected from pre-approved panel
  - Arbitrator has access to full evidence, reputation algorithms, transaction history
  - Decision is final and binding
  - AURA covers arbitration cost if decision reverses Human Review

8.2 Reputation Appeal Categories

Category 1: Algorithmic Error

Claim: "The reputation calculation is mathematically incorrect"
Evidence Required: Specific formula and data showing miscalculation
Resolution Time: 5 business days (automated audit of calculation)
Success Rate: ~5% (most calculations are correct)

Category 2: Mitigating Circumstances

Claim: "Negative event was beyond my control"
Examples:
  - Beacon late delivery due to carrier failure (tracking evidence)
  - Scout payment delay due to bank system outage (bank statement)
  - Force majeure events (natural disaster, pandemic impact)
Evidence Required: Third-party documentation of circumstances
Resolution Time: 10 business days (verification of evidence)
Success Rate: ~15% (genuinely beyond control)

Category 3: Data Integrity Issue

Claim: "The transaction data used for scoring is inaccurate"
Examples:
  - Duplicate penalty for same incident
  - Transaction attributed to wrong agent
  - Scout review posted by wrong person
Evidence Required: System logs, transaction records, communication history
Resolution Time: 7 business days (data forensics)
Success Rate: ~8% (data integrity usually reliable)

Category 4: Policy Interpretation

Claim: "The reputation policy was applied incorrectly to my situation"
Examples:
  - Unclear edge case in reputation specification
  - Conflicting guidance from platform support
  - Reasonable interpretation of ambiguous policy
Evidence Required: Policy excerpts, communication with AURA support
Resolution Time: 14 business days (policy team review)
Success Rate: ~20% (policy ambiguities do occur)

Category 5: Procedural Fairness

Claim: "I was not given opportunity to respond before reputation penalty"
Examples:
  - No notification of pending reputation impact
  - Insufficient time to provide counter-evidence
  - Lack of clear explanation for penalty
Evidence Required: Communication records, notification logs
Resolution Time: 7 business days (process audit)
Success Rate: ~10% (notification systems generally reliable)

8.3 Appeals Outcomes

Full Reversal:

Partial Reversal:

Upheld:

Enhanced Penalty:

8.4 Reputation Amnesty Programs

Good Faith Rehabilitation:

For agents with BR/SR < 50 who demonstrate commitment to improvement:
  - Enroll in 90-day rehabilitation program
  - Meet behavioral milestones (e.g., 20 consecutive successful transactions)
  - Receive 10-point reputation bonus upon successful completion
  - One-time opportunity per agent lifetime

Systemic Issue Forgiveness:

If platform-wide issue caused reputation damage:
  - AURA may declare "reputation amnesty period"
  - Affected agents receive partial or full reputation restoration
  - Example: Platform outage causing Beacon fulfillment delays → TE penalty waived

Fresh Start (Rare):

In exceptional cases (e.g., agent faced personal crisis, documented hardship):
  - Can apply for reputation reset to tier baseline (SR = 72.75, BR = 76)
  - Requires:
    - Minimum 6 months since last major violation
    - Completion of appeals process
    - Executive review and approval
  - Granted <1% of applications (truly exceptional circumstances only)

8.5 Transparency and Communication

Reputation Change Notifications:

All agents receive real-time notification when reputation changes:
  - Magnitude of change: +X or -X points
  - Affected dimension(s): "Transaction Reliability decreased by 5 points"
  - Reason: "Late delivery on Order #12345 (3 days past promised date)"
  - Impact: "You've moved from Gold tier (SR 78) to Silver tier (SR 73)"
  - Next steps: "To recover, focus on on-time delivery. See improvement guide."

Reputation Dashboard:

Each agent has access to detailed reputation dashboard:
  - Current SR/BR with dimensional breakdown
  - Historical reputation trend (past 12 months)
  - Comparison to category averages
  - Specific actions to improve each dimension
  - Projected tier if current trajectory continues

Educational Resources:

AURA provides comprehensive reputation guidance:
  - "How Reputation Works" video tutorial
  - Dimension-specific improvement guides
  - Case studies of successful rehabilitation
  - FAQ addressing common concerns
  - Live webinars with Q&A for new agents

9. Implementation Guidelines

9.1 Technical Architecture

Data Storage:

Reputation Data Store (Distributed Ledger):
  - Immutable transaction history
  - Versioned reputation scores (time-series)
  - Dimensional score history per agent
  - Appeals and dispute records
  
Reputation Calculation Engine:
  - Real-time score updates for transaction events
  - Batch processing for daily/weekly/monthly calculations
  - Audit trail of all reputation changes
  - Rollback capability for erroneous calculations
  
Reputation API:
  - GET /reputation/{agent_id} → Returns current reputation vector
  - GET /reputation/{agent_id}/history → Returns time-series reputation data
  - GET /reputation/{agent_id}/transactions → Returns reputation-relevant transaction history
  - POST /reputation/dispute → Initiates dispute process

Integration Points:

AURA Core Integration:
  1. Model Management → Reputation-weighted profile data for agent matching
  2. Market Navigation Engine → CWR scores for Beacon ranking
  3. Transaction Services → Reputation updates on transaction lifecycle events
  4. Compliance & Privacy → Reputation data handling, audit logs
  5. Network Health Monitor → Population metrics, intervention triggers

Security & Privacy:

Access Control:
  - Agents can view own full reputation detail
  - Agents can view counterparty's aggregate reputation (SR/BR), not dimensional breakdown
  - AURA internal systems access dimensional data for matching, interventions
  - Dispute reviewers access full reputation + transaction history on need-to-know basis
  
Data Retention:
  - Reputation scores: Retained indefinitely (core platform data)
  - Transaction history: Retained per regulatory requirements (e.g., 7 years)
  - Dispute records: Retained for life of agent account + 3 years after closure

9.2 Development Roadmap

Phase 1: Foundation (Q1 2026)

Phase 2: Matching Integration (Q2 2026)

Phase 3: Incentives & Governance (Q3 2026)

Phase 4: Network Health (Q4 2026)

Phase 5: Optimization & Scale (2027)

9.3 Testing & Validation

Unit Testing:

Test reputation calculation formulas:
  - Verify SR and BR calculations with known inputs
  - Test edge cases (zero transactions, maximum penalties, etc.)
  - Validate decay functions over time
  - Check tier boundary conditions (e.g., SR = 89.99 vs 90.00)

Integration Testing:

Test reputation system with other AURA components:
  - Reputation updates trigger correctly on transaction events
  - CWR scores influence Beacon ranking as expected
  - Profile compatibility calculations integrate reputation properly
  - Network health metrics respond to population changes

User Acceptance Testing:

Beta program with real Scouts and Beacons:
  - Collect feedback on reputation dashboard clarity
  - Validate that reputation changes feel fair and explainable
  - Test dispute resolution process with real cases
  - Measure impact on agent behavior (are incentives working?)

Simulation Testing:

Agent-based modeling to stress-test reputation system:
  - Simulate 10,000 Scouts and 1,000 Beacons over 1-year period
  - Model various gaming strategies and verify detection
  - Test population health under different growth scenarios
  - Validate that "nice" cooperative behavior is rewarded over rational optimization

9.4 Monitoring & Metrics

Reputation Health Metrics:

Daily Monitoring:
  - Average SR and BR across population
  - Distribution of agents across tiers
  - Reputation change velocity (avg points changed per day)
  - Dispute rate (appeals per 1,000 transactions)
  
Weekly Monitoring:
  - Reputation inflation/deflation trends
  - Tier mobility (how many agents move up/down tiers)
  - Rehabilitation program success rate
  - Gaming detection hits and false positive rate
  
Monthly Monitoring:
  - SPH and BPH scores
  - Correlation between reputation and transaction outcomes
  - Appeals resolution time and outcome distribution
  - Impact of reputation on Scout retention and Beacon GMV

Success Metrics:

Reputation System Goals:
  1. Predictive Validity: High-reputation agents should have better outcomes
     - Measure: Correlation between BR and Scout satisfaction (target: r > 0.60)
  2. Incentive Alignment: Reputation should drive positive behavior
     - Measure: % of Beacons improving reputation over time (target: >60%)
  3. Fairness: Reputation should not systematically disadvantage groups
     - Measure: FM scores stable across Beacon demographics (target: avg FM > 75)
  4. Trust: Agents should understand and trust reputation system
     - Measure: Agent survey "I trust AURA's reputation system" (target: >70% agree)
  5. Network Health: Ecosystem should maintain quality over time
     - Measure: SPH > 70, BPH > 75 sustained for 12 consecutive months

9.5 Documentation Requirements

For Engineering Team:

For Product & Business Teams:

For Academic Partners:

10. Appendices

Appendix A: Formula Reference

Scout Reputation Total:

SR = (0.25 × EI) + (0.30 × TR) + (0.20 × PC) + (0.15 × NC) + (0.10 × VA)

Engagement Integrity:

EI = 100 × (Completed_Engagements / Initiated_Engagements) × Recency_Weight
Recency_Weight = Σ(w_i × e^(-λt_i)) / Σ(e^(-λt_i)) where λ = 0.01

Transaction Reliability:

TR = (0.5 × Completion_Rate + 0.3 × Payment_Timeliness + 0.2 × Cancellation_Avoidance) × 100

Profile Consistency:

PC = 100 × (1 - Divergence_Score) × Temporal_Stability
Divergence_Score = Σ(|Profile_Weight_i - Behavioral_Weight_i|) / N_dimensions

Network Contribution:

NC = (0.4 × Feedback_Quality + 0.3 × Dispute_Fairness + 0.3 × Community_Value) × 100

Values Authenticity:

VA = 100 × [1 - (Σ|Stated_v - Purchase_v| / N_values_dimensions)]

Beacon Reputation Total:

BR = (0.25 × OQ) + (0.30 × TE) + (0.20 × TS) + (0.15 × FM) + (0.10 × NS)

Offer Quality:

OQ = (0.4 × Relevance_Score + 0.35 × Competitiveness + 0.25 × Offer_Integrity) × 100

Transaction Excellence:

TE = (0.4 × Fulfillment_Score + 0.35 × Service_Quality + 0.25 × Issue_Resolution) × 100

Transparency Score:

TS = (0.5 × Description_Accuracy + 0.3 × Terms_Clarity + 0.2 × Disclosure_Completeness) × 100

Fairness Metric:

FM = 100 × (1 - Price_Discrimination_Score) × Service_Equality_Score

Network Stewardship:

NS = (0.35 × Protocol_Compliance + 0.30 × Data_Quality + 0.20 × Innovation_Participation + 0.15 × Community_Support) × 100

Compatibility-Weighted Reputation:

CWR = (Base_Reputation × 0.6) + (Compatibility_Score × 0.4)
Compatibility_Score = Profile_Alignment × Values_Alignment

Reputation Decay (Scout):

If Days_Inactive > 180: SR_new = SR_old × (0.99)^((Days - 180) / 30)

Reputation Decay (Beacon):

If Days_Inactive > 90: BR_new = BR_old × (0.98)^((Days - 90) / 30)

Appendix B: Threshold Tables

Scout Reputation Tiers: | SR Range | Tier | Percentile (Target) | |———-|——|———————| | 90-100 | Platinum | Top 10% | | 75-89 | Gold | 25th-90th percentile | | 60-74 | Silver | 40th-75th percentile | | 40-59 | Bronze | 20th-60th percentile | | 20-39 | Probation | Bottom 20% |

Beacon Reputation Tiers: | BR Range | Tier | Percentile (Target) | |———-|——|———————| | 90-100 | Elite | Top 10% | | 75-89 | Premier | 25th-90th percentile | | 60-74 | Standard | 40th-75th percentile | | 40-59 | Developing | 20th-60th percentile | | 20-39 | Restricted | Bottom 20% |

Appendix C: Penalty Reference Guide

Scout Penalties: | Violation | Points | Recovery Time* | |———–|——–|—————-| | Engagement Abandonment | -2 | 2 weeks | | Pattern (3+ in 30 days) | -5 additional | 1 month | | Ghost After Personalized Offer | -10 | 5 weeks | | Payment Delay (1-3 days) | -3 | 2 weeks | | Payment Delay (4-7 days) | -7 | 3 weeks | | Payment Delay (8+ days) | -12 | 6 weeks | | Post-Acceptance Cancellation | -15 | 7 weeks | | Disputed Chargeback | -25 | 12 weeks |

*Recovery Time = estimated weeks to recover points through positive behavior

Beacon Penalties: | Violation | Points | Recovery Time* | |———–|——–|—————-| | Spam Offer (5+ rejections) | -5 | 3 weeks | | Hidden Fee Complaint | -10 | 5 weeks | | Late Delivery (1-3 days) | -2 | 1 week | | Late Delivery (4-7 days) | -5 | 2 weeks | | Late Delivery (8+ days) | -10 | 5 weeks | | Product Mismatch | -12 | 6 weeks | | Damaged/Wrong Item | -15 | 7 weeks | | Unclear Return Policy → Dispute | -10 | 5 weeks | | Misleading Product Claim | -20 | 10 weeks | | Unresolved Issue (14+ days) | -20 | 10 weeks | | Seller Cancellation Post-Acceptance | -25 | 12 weeks | | Confirmed Bait-and-Switch | -30 | 15 weeks | | Confirmed Price Discrimination | -30 | 15 weeks + review |

*Recovery Time = estimated weeks to recover points through positive behavior

Appendix D: Glossary

Agent: Autonomous software entity representing either Scout (buyer) or Beacon (seller) interests

AURA Core: Central infrastructure layer managing Scout-Beacon interactions, including reputation system

Beacon: Seller-side agent representing seller interests, making offers to Scouts

Behavioral Weight: Inferred preference importance derived from actual purchase behavior (vs stated preferences)

Compatibility-Weighted Reputation (CWR): Composite score combining base reputation with profile compatibility for matching

Constraint Engine: AURA component filtering product options based on Scout constraints and preferences

Dimensional Reputation: Multi-attribute reputation vector capturing different aspects of agent behavior

Engagement Integrity: Scout reputation dimension measuring follow-through on shopping intent

Fairness Metric: Beacon reputation dimension measuring equitable treatment across Scout segments

Folk Theorem: Game theory result showing cooperation is sustainable in repeated interactions with reputation

Market Navigation Engine: AURA component surfacing relevant Beacon offers to Scouts based on CWR

Network Contribution: Reputation dimension measuring ecosystem participation quality

Offer Quality: Beacon reputation dimension measuring relevance and honesty of offers

Profile Consistency: Scout reputation dimension measuring alignment between stated and revealed preferences

Scout: Buyer-side agent representing buyer interests, searching for products on behalf of user

Shadow of the Future: Game theory concept where future interaction expectations influence current behavior

Transaction Excellence: Beacon reputation dimension measuring fulfillment and service quality

Transparency Score: Beacon reputation dimension measuring honesty in product representation

Values Authenticity: Scout reputation dimension measuring consistency between stated values and purchases

Appendix E: Academic References

This reputation system draws on established research in behavioral economics, game theory, and market design:

Behavioral Economics:

Game Theory & Reputation:

Market Design:

E-Commerce Reputation Systems:

Appendix F: Change Log

Version 1.0 (November 10, 2025)

Future Versions:

Document Approval

Author: Marc Massar, AURA Labs Architecture Team
Reviewed By: [Pending]
Approved By: [Pending]
Next Review Date: Q2 2026

End of Specification