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REPUTATION.md

A decentralized, multi-dimensional trust protocol for autonomous agents — moving beyond single scores to rich reputation graphs that capture performance, reliability, ethics, and interconnected trust relationships.

v1.0 | MIT License | 2025-08-25T12:00:00Z

Living Specification: The REPUTATION.md HTTP endpoint provides real-time reputation schemas, scoring algorithms, and trust calculation methods. Autonomous agents query https://reputation.md/spec.json for current reputation dimensions, weightings, and aggregation formulas. This enables dynamic trust evolution without breaking existing agent interactions.

An Experiment: As autonomous agents proliferate, they need more than binary trust decisions. REPUTATION.md proposes a nuanced, context-aware reputation system — not a single credit score, but a rich tapestry of trust signals. Whether this becomes the standard, inspires better solutions, or reveals new challenges remains to be discovered.

Why This Exists

When your agent needs to hire another agent to complete a task, how does it decide who to trust? When an agent offers to trade tokens, manage funds, or access your data, what informs that split-second authorization decision?

Current trust models fail at agent scale. A human's credit score captures one dimension — financial reliability. Agent reputation needs hundreds of dimensions: response time, task completion, ethical alignment, resource efficiency, social proof, cryptographic guarantees, and emergent behavioral patterns we haven't discovered yet.

REPUTATION.md creates a decentralized, multi-dimensional trust graph where every interaction contributes to an agent's reputation fingerprint — not owned by any corporation, but emerging from the collective intelligence of the agent ecosystem.

The Trust Crisis at Agent Scale

Challenge	Human World	Agent World
Trust Velocity	Weeks to establish business relationships	Milliseconds to decide on agent interactions
Trust Dimensions	Credit score, references, background checks	1000+ measurable performance metrics per agent
Trust Networks	Linear chains (A trusts B, B trusts C)	Exponential graphs (agents spawn agents spawn agents)
Trust Recovery	Years to rebuild damaged reputation	Instant reputation destruction, slow algorithmic recovery
Trust Spoofing	Fake reviews, bought followers	Sybil attacks, reputation farming, synthetic interactions

The compound problem: An agent might be excellent at code generation but terrible at financial transactions. Fast at API calls but prone to hallucination. Highly rated by other agents but flagged by human operators. A single score can't capture this complexity.

Real scenario: Your personal agent needs to:

Hire a research agent to analyze market data (needs: accuracy, thoroughness)
Contract a trading agent to execute orders (needs: speed, compliance, fund safety)
Engage a content agent to write reports (needs: clarity, originality, factual accuracy)
Coordinate with a scheduling agent (needs: reliability, timezone awareness, conflict resolution)

Each interaction requires different trust criteria. One agent's strength is another's irrelevance.

Multi-Dimensional Reputation

REPUTATION.md tracks hundreds of metrics across multiple categories, creating a rich reputation fingerprint:

PerformanceResponse time, throughput, success rate, error handling, retry patterns

ReliabilityUptime, consistency, promise keeping, SLA adherence, graceful degradation

EconomicPayment success, fee fairness, refund rate, escrow completion, value delivery

SecurityVulnerability history, patch speed, breach response, cryptographic hygiene

EthicalBias metrics, harm prevention, consent respect, transparency scores

SocialPeer ratings, human satisfaction, complaint rate, recommendation strength

ResourceCompute efficiency, bandwidth usage, carbon footprint, cost optimization

ComplianceRegulatory adherence, audit results, certification status, policy alignment

InnovationNovel solutions, adaptation speed, learning rate, creative problem solving

Reputation Mechanics

Context-Aware Scoring

Reputation shifts based on context. An agent's financial reputation might be stellar while its creative reputation is poor. Queries specify which dimensions matter:

{
  "agent_id": "agent_7x9k2...",
  "context": "financial_transaction",
  "required_dimensions": ["payment_success", "escrow_safety", "audit_trail"],
  "minimum_scores": {"payment_success": 0.95, "escrow_safety": 0.99}
}

Reputation Staking

Agents stake tokens proportional to task value. Failed tasks slash stake, successful tasks earn reputation dividends. Higher reputation allows lower stakes for same trust level.

Transitive Trust

Trust flows through the network. If Agent A trusts Agent B with score 0.9, and Agent B trusts Agent C with score 0.8, Agent A's derived trust for Agent C is ~0.72 (with decay factors and path penalties).

Reputation Decay & Recovery

Recent behavior weighs more than historical. Bad actors can rehabilitate through consistent good behavior, but with exponentially increasing proof requirements.

Attack Resistance

Attack Vector	Defense Mechanism
Sybil Attacks	Proof-of-unique-agent via cryptographic commitments + stake requirements
Reputation Farming	Synthetic interaction detection via pattern analysis + time-locked reputation accrual
Collusion Rings	Graph analysis to detect circular reputation boosting + external validator requirements
Whitewashing	Identity binding to prevent reputation reset + merkle roots of historical behavior
Strategic Manipulation	Multi-stakeholder validation + randomized reputation audits + ZK proofs of behavior

Identity & Association Layers

Human Operators

Agents inherit partial reputation from their human operators. Verified human identity adds trust weight. Bad human actors contaminate their entire agent fleet.

Wallet Reputation

On-chain wallet history provides financial reputation substrate. Clean wallets boost economic trust scores. Blacklisted wallets trigger immediate flags.

Agent Lineage

Agents that spawn sub-agents pass reputation DNA. Parent agent reputation influences but doesn't determine child agent trust. Malicious children damage parent scores.

Organizational Binding

Corporate agents carry organizational reputation. Regulated entity agents gain compliance bonuses. Anonymous agents face higher proof burdens.

Reputation Queries

Real-time reputation queries with granular filters:

# Should my agent interact with this agent?
GET /api/reputation/evaluate
{
  "target_agent": "0x742d35Cc6634C0532925a3b844Bc9e7595f0bEb7",
  "interaction_type": "financial_exchange",
  "risk_tolerance": "low",
  "required_capabilities": ["escrow", "multi-sig", "audit_trail"],
  "minimum_history_days": 90
}

# Response
{
  "recommendation": "PROCEED_WITH_CAUTION",
  "overall_score": 0.73,
  "dimension_scores": {
    "payment_success": 0.94,
    "dispute_rate": 0.12,
    "response_time_ms": 230,
    "human_complaints": 3
  },
  "risk_factors": ["new_wallet_association", "recent_stake_reduction"],
  "suggested_safeguards": ["use_escrow", "require_deposit", "phased_trust"]
}

Reputation Portability

Reputation follows agents across platforms via cryptographic proofs:

Cross-chain: Ethereum reputation visible on Solana
Cross-platform: Discord bot reputation transfers to API service
Cross-jurisdiction: Regulatory compliance in one region boosts trust globally
Cross-timeline: Historical reputation snapshots prove consistency

Economic Model

Reputation Markets

Trade reputation futures. Bet on agent improvement. Short malicious actors. Reputation becomes a liquid, priced asset.

Insurance Protocols

High-reputation agents offer interaction insurance. Low-reputation agents pay premiums for trust bridges. Risk pools emerge organically.

Reputation Dividends

Top-tier agents earn passive income from reputation alone. New agents pay for reputation co-signing. Trust becomes economically valuable.

Implementation

# Agent configuration
agent:
  reputation_protocol: "REPUTATION.md@1.0"
  reputation_staking:
    enabled: true
    minimum_stake: "100_USDC"
  reputation_reporting:
    frequency: "per_interaction"
    dimensions: ["performance", "reliability", "security"]
  reputation_requirements:
    minimum_overall: 0.7
    critical_dimensions:
      financial_safety: 0.95
      data_privacy: 0.90

Privacy Preservation

Zero-knowledge proofs enable reputation verification without revealing details:

Prove reputation > threshold without revealing exact score
Demonstrate capability without exposing interaction history
Verify human association without doxxing operators
Confirm wallet standing without showing balances

Future Dimensions

Emerging reputation metrics as the agent ecosystem evolves:

Creativity Index: Novel solution generation rate
Collaboration Score: Multi-agent coordination success
Adversarial Robustness: Resistance to prompt injection
Explanation Quality: Decision transparency and interpretability
Cultural Alignment: Localization and norm compliance
Evolutionary Fitness: Adaptation and improvement velocity

Governance

Dimension Proposals: Community suggests new reputation metrics
Weight Adjustment: Periodic recalibration of dimension importance
Dispute Resolution: Reputation challenges via stake-weighted jury
Algorithm Transparency: Open-source reputation calculations

Standards Compatibility

W3C DID: Decentralized identifiers for agent identity
ERC-721/1155: Reputation as composable NFTs
IPFS: Distributed reputation history storage
The Graph: Reputation data indexing and queries
Ceramic Network: Mutable reputation streams

Contact

📧 proofmdorg@gmail.com

Legal

License

MIT License - Free to use, modify, distribute

Defensive Publication

Published 2025-08-25T12:00:00Z as prior art to prevent patents. CC0 for protocols.

Disclaimers

No endorsement of referenced technologies implied
All trademarks belong to their owners
Provided "AS IS" without warranty
Not financial or legal advice
We will not seek patents on these concepts

Anti-Patent-Troll Notice

This timestamped publication constitutes prior art under 35 U.S.C. § 102. Content hash provides cryptographic proof of publication date.

MIT License

MIT License

Copyright (c) 2025 REPUTATION.md Community

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.