A trust score is a summary of the signals a system has captured about an agent. Its value depends on the factors, history, and interpretation behind it. A high score is not a guarantee that the next answer or action will be correct.
Inspect the evidence behind the number
Ask which factors contributed to the result, which events were observed, and whether the history is representative of the task you are considering. An agent used for low-risk document summaries has not thereby demonstrated suitability to authorize a financial transaction.
The Truthlocks console presents agent scores and available supporting factors. Follow the displayed scale and field definitions in your integration. If an API returns a normalized value, do not compare it with a percentage threshold without applying the documented conversion.
Missing history is not a success signal
A new agent may have little recorded activity. A disconnected tool may report no useful events. Neither condition should be displayed as a clean operational record. Keep unavailable data distinct from a measured result so reviewers understand the limits of the score.
When investigating a change, use available history and action records. Avoid inventing a trend from one current value or treating an absent history endpoint as evidence of consistent performance.
Keep authorization separate
Permissions should be defined and enforced by the tools responsible for the action. A score can inform a review or a configured policy, but it should not silently replace required approval, scope checks, or task-specific evidence.
For a lending recommendation, the reviewer needs the application evidence, permitted agent task, captured reasoning or references, and the organization’s decision criteria. The agent’s operational history is context within that review, not the lending decision itself.
Review scores alongside concrete events
- Confirm the agent identity and the intended assignment.
- Inspect the score’s available factors and historical coverage.
- Follow the relevant action receipts and exceptions.
- Apply the receiving system’s authorization and review requirements.
- Record why the reviewer accepted, limited, or stopped the proposed work.
Explore automated lending recommendations and machine identity to put a score in its proper operational context.