intertrust

Track AI agent trust scores with severity-weighted decay in SQLite.

3|1|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/mistakeknot/Demarch --skill intertrust
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: intertrust
Source: https://github.com/mistakeknot/Demarch/tree/main/.gemini/generated-skills/intertrust
Command: npx skills add https://github.com/mistakeknot/Demarch --skill intertrust

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of managing and evaluating the reliability of AI agents by providing a robust system for tracking their performance and reputation.

Core Features & Use Cases

  • Reputation Tracking: Monitors agent performance through feedback on findings and their severity.
  • Severity-Weighted Decay: Applies a decay mechanism to trust scores, giving more weight to recent and severe findings.
  • Suppression Candidates: Identifies agents that may require closer monitoring or intervention.
  • Use Case: In a multi-agent development environment, this Skill helps identify which agents are consistently producing high-quality, accepted code versus those that frequently introduce issues, allowing for targeted improvements or reassignments.

Quick Start

Check the current trust status for all agents in the 'my-project' project.

Frequently Asked Questions about intertrust

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track AI agent reputation and trust scores in a development lifecycle?▼

Agent trust scoring tracks AI agent reputation by storing feedback in a SQLite database, applying a blended algorithm with severity-weighted decay to evaluate historical performance and reliability.

What is severity-weighted decay in agent trust scoring?▼

Severity-weighted decay is a scoring mechanism that applies time-based decay to trust scores, giving more weight to recent and severe findings to evaluate agent reliability.

How do I identify AI agents that need closer monitoring or intervention?▼

Suppression candidates are identified by analyzing historical performance data and trust feedback, flagging agents that frequently introduce issues for targeted improvements or reassignments.

Can I use a SQLite database for storing multi-agent trust feedback?▼

Yes, agent trust scoring utilizes a shared SQLite database for storing trust feedback, calculating project-specific and global scores using a blended algorithm with time-based decay.

Does agent trust scoring evaluate both project-specific and global performance?▼

Yes, the trust scoring algorithm blends project-specific and global scores, incorporating time-based decay to provide a comprehensive evaluation of agent performance across environments.

When do I need agent trust scoring for my development workflow?▼

Agent trust scoring is needed in multi-agent development environments to identify which agents consistently produce accepted code versus those that frequently introduce issues.