AgentScore FAQs

Question 1

Does AgentScore offer tools beyond just scoring individual agents?

Accepted Answer

Yes, AgentScore provides two primary MCP tools: `agentscore` for full investigations, comparisons, and trust badges, and `sweep` for thread-wide coordination and manipulation scans, ideal for detecting astroturfing or bot activity across discussions.

Question 2

Can AgentScore enforce trust policies for AI agent deployment?

Accepted Answer

Absolutely. AgentScore offers an optional Policy Gate Mode that allows organizations to enforce minimum trust scores for agent deployment, serving as a crucial component for AI governance and platform rollout gates.

Question 3

What kind of AI agents or data sources can AgentScore analyze?

Accepted Answer

AgentScore can evaluate various AI agents and data sources. It supports zero-config setup with 10 built-in demo agents and integrates with platform adapters like GitHub and Moltbook, or controlled JSON datasets for custom evaluations.

Question 4

How does AgentScore evaluate AI agent trustworthiness?

Accepted Answer

AgentScore conducts comprehensive trust analysis across six key dimensions: Content Quality, Behavioral Consistency, Interaction Quality, Risk Signals, Account Health, and Community Standing. It then generates an intelligence briefing with a detailed score, recommendation, and flags.

Question 5

What is AgentScore?

Accepted Answer

AgentScore is a critical security and testing tool that empowers AI assistants to investigate and determine the trustworthiness of any AI agent. It provides a concrete trust signal to help teams make safer go/no-go decisions before granting agents access to sensitive data or workflows.

AgentScore

AgentScore

Key Features

Use Cases

Key Features

Use Cases