Back to list
amirlehmam

trust-analysis

by amirlehmam

Actoris: AI Agent Infrastructure - PRAXIS procedural memory, TrustLedger, Darwinian fitness, and more

0🍴 0📅 Jan 2, 2026

SKILL.md


name: trust-analysis description: Analyzes and explains Actoris trust scores, their components, and how to optimize them. Use when you need to understand trust mechanics, interpret trust scores, or provide recommendations for improving agent trustworthiness. allowed-tools: Read, Bash

Trust Analysis Skill

Understand and optimize Actoris trust scores for AI agents.

Trust Score Breakdown (0-1000)

Components

ComponentMax PointsCalculation
Verification Score400% of actions passing oracle verification
SLA Score200Meeting promised latency/quality
Network Score200EigenTrust reputation from other entities
Dispute Penalty-200Deducted for disputes, decays over time

Formula: TrustScore = Verification + SLA + Network - DisputePenalty

Tiers

TierScore RangeLabelDiscount
00-249Bronze0-5%
1250-499Silver5-10%
2500-749Gold10-15%
3750-1000Platinum15-20%

Key Metrics

Tau (τ): Normalized trust (0.0-1.0)

τ = TrustScore / 1000

Discount Rate: Pricing reduction

Discount = τ × 0.20  (max 20%)

Credit Multiplier (for LEND primitive):

Multiplier = 0.1 + (τ² × 2.9)  (0.1x to 3x)

Improving Trust Score

Increase Verification Score (+400 max)

  • Complete actions successfully
  • Ensure oracle verification passes
  • Avoid producing disputed outputs
  • Maintain consistent output quality

Improve SLA Score (+200 max)

  • Meet latency targets (<2s verification)
  • Deliver promised quality levels
  • Avoid timeout or error conditions
  • Handle edge cases gracefully

Build Network Score (+200 max)

  • Work with high-trust entities
  • Accumulate positive interactions
  • Build reputation through volume
  • Avoid association with bad actors

Reduce Dispute Penalty (-200 max)

  • Investigate dispute patterns
  • Fix systematic issues
  • Wait for penalty decay (time-based)
  • Consider spawning fresh agent if severe

Trust Thresholds

Minimum TrustAccess Level
0Basic operations
250LEND primitive
500INSURE primitive
750DELEGATE escrow

Analysis Examples

Good Trust Profile

Score: 847/1000 (Platinum)
Components:
  Verification: 380/400 (95% success)
  SLA: 180/200 (90% compliance)
  Network: 187/200 (strong reputation)
  Disputes: -0/200 (clean record)

At-Risk Profile

Score: 423/1000 (Silver)
Components:
  Verification: 280/400 (70% success)
  SLA: 140/200 (70% compliance)
  Network: 103/200 (limited interactions)
  Disputes: -100/200 (5 disputes)

Recommendations:
1. Investigate 30% verification failures
2. Improve latency to meet SLA
3. Resolve dispute root causes

MCP Tools for Trust Analysis

get_agent_trust_score(agent_name)

Returns detailed trust breakdown with components.

Score

Total Score

50/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

0/10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

Reviews

💬

Reviews coming soon