How do I install the Trust Analysis skill?

Run npx skillmds@latest add majiayu000/trust-analysis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Trust Analysis safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Trust Analysis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Trust Analysis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Trust Analysis?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Trust Analysis by majiayu000 — Agent Skill

Name: Trust Analysis
Rating: 4.5 (4 reviews)
Author: majiayu000

Trust Analysis

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.

majiayu000 Updated Sep 9, 2026 567 repo stars

File contents

Trust Analysis Skill

Understand and optimize Actoris trust scores for AI agents.

Trust Score Breakdown (0-1000)

Components

Component	Max Points	Calculation
Verification Score	400	% of actions passing oracle verification
SLA Score	200	Meeting promised latency/quality
Network Score	200	EigenTrust reputation from other entities
Dispute Penalty	-200	Deducted for disputes, decays over time

Formula: TrustScore = Verification + SLA + Network - DisputePenalty

Tiers

Tier	Score Range	Label	Discount
0	0-249	Bronze	0-5%
1	250-499	Silver	5-10%
2	500-749	Gold	10-15%
3	750-1000	Platinum	15-20%

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 Trust	Access Level
0	Basic operations
250	LEND primitive
500	INSURE primitive
750	DELEGATE 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.

---name: trust-analysisdescription: 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.--- # Trust Analysis Skill Understand and optimize Actoris trust scores for AI agents. ## Trust Score Breakdown (0-1000) ### Components | Component | Max Points | Calculation | |-----------|------------|-------------| | Verification Score | 400 | % of actions passing oracle verification | | SLA Score | 200 | Meeting promised latency/quality | | Network Score | 200 | EigenTrust reputation from other entities | | Dispute Penalty | -200 | Deducted for disputes, decays over time | **Formula**: `TrustScore = Verification + SLA + Network - DisputePenalty` ### Tiers | Tier | Score Range | Label | Discount | |------|-------------|-------|----------| | 0 | 0-249 | Bronze | 0-5% | | 1 | 250-499 | Silver | 5-10% | | 2 | 500-749 | Gold | 10-15% | | 3 | 750-1000 | Platinum | 15-20% | ### 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 Trust | Access Level | |---------------|--------------| | 0 | Basic operations | | 250 | LEND primitive | | 500 | INSURE primitive | | 750 | DELEGATE 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.

Frequently asked questions