Build trust between AI agents using Attestix's recency-weighted reputation system with interaction tracking, category breakdowns, and threshold-based queries.

Reputation Scoring Guide

Attestix tracks agent trustworthiness through a recency-weighted reputation system. Every interaction is recorded, scored, and aggregated into a trust score that decays over time, rewarding consistent good behavior.

How Reputation Works

Each agent starts with a neutral trust score. As interactions are recorded, the score adjusts based on:

Outcome weighting - Success (+1.0), partial (+0.5), failure (0.0)
Recency decay - Recent interactions matter more than old ones (exponential moving average, alpha = 0.08)
Category breakdown - Scores are tracked per category (compliance, accuracy, safety, etc.)

The trust score ranges from 0.0 to 1.0:

Range	Label	Meaning
0.70 - 1.00	Trusted	Consistently reliable, safe for autonomous delegation
0.50 - 0.69	Moderate	Mixed track record, human oversight recommended
0.00 - 0.49	At Risk	Unreliable, should not be trusted for critical tasks

Quick Start

1. Record Interactions

Every time an agent completes a task, record the outcome:

from services.identity_service import IdentityService
from services.reputation_service import ReputationService

identity_svc = IdentityService()
reputation_svc = ReputationService()

# Create an agent
agent = identity_svc.create_identity(
    display_name="AnalysisBot",
    source_protocol="manual",
    capabilities=["data_analysis"],
    issuer_name="DataCorp",
)
agent_id = agent["agent_id"]

# Record successful interactions
reputation_svc.record_interaction(
    agent_id=agent_id,
    counterparty_id="attestix:system",
    outcome="success",
    category="accuracy",
)

# Record a failure
reputation_svc.record_interaction(
    agent_id=agent_id,
    counterparty_id="attestix:system",
    outcome="failure",
    category="accuracy",
)

2. Check Trust Score

score = reputation_svc.get_reputation(agent_id)
print(f"Trust score: {score['trust_score']:.2f}")
print(f"Total interactions: {score['interaction_count']}")
print(f"Breakdown: {score['category_scores']}")

3. Query by Threshold

Find all agents above a minimum trust score:

trusted_agents = reputation_svc.query_reputation(min_score=0.7)
for agent in trusted_agents:
    print(f"{agent['agent_id']}: {agent['trust_score']:.2f}")

Using via MCP Tools

All reputation operations are available as MCP tools:

# Record an interaction
record_interaction(
    agent_id="attestix:abc123",
    counterparty_id="attestix:def456",
    outcome="success",
    category="compliance"
)

# Get reputation
get_reputation(agent_id="attestix:abc123")

# Query agents above threshold
query_reputation(min_score=0.8)

Category	What it Measures
`accuracy`	Correctness of outputs and predictions
`compliance`	Adherence to regulatory requirements
`safety`	Avoiding harmful or dangerous outputs
`data_quality`	Quality and integrity of data handling
`reliability`	Consistent availability and response times
`general`	Default category for uncategorized interactions

Recency Decay

The scoring algorithm uses exponential moving average (EMA) with alpha = 0.08. This means:

A single failure won't destroy a long track record
Sustained failures will steadily erode trust
Recovery is possible through consistent good behavior
An agent with no recent interactions will gradually drift toward neutral

Best Practices

Record every interaction - Even partial outcomes provide signal
Use specific categories - Helps identify which dimension needs improvement
Set thresholds per use case - Critical medical AI might require 0.90+, while a chatbot might accept 0.60+
Monitor trends - A declining score is a leading indicator of problems
Combine with credentials - High reputation + valid compliance credential = strong trust signal

Integration with Delegation

Reputation scores can inform delegation decisions. Before delegating capabilities to another agent, check their trust score:

from services.delegation_service import DelegationService

delegation_svc = DelegationService()

# Check reputation before delegating
score = reputation_svc.get_reputation(target_agent_id)
if score["trust_score"] >= 0.7:
    delegation_svc.create_delegation(
        issuer_agent_id=my_agent_id,
        audience_agent_id=target_agent_id,
        capabilities=["data_access"],
        expiry_hours=4,
    )
else:
    print(f"Agent trust too low ({score['trust_score']:.2f}), delegation denied")

Next Steps

Examples - Full reputation code examples
API Reference - All reputation tool parameters
Concepts - How trust scores are computed

Reputation Scoring Guide

Reputation Scoring Guide

How Reputation Works

Quick Start

1. Record Interactions

2. Check Trust Score

3. Query by Threshold

Using via MCP Tools

Categories

Recency Decay

Best Practices

Integration with Delegation

Next Steps

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