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by vorionsys

vorion_check_trust

Check an AI agent's trust score and tier before allowing sensitive actions. Returns numeric score, tier number and name, and observation tier from the Vorion governance system.

Instructions

Look up an AI agent's current trust score and tier in the Vorion governance system. Returns the numeric score (0-1000), tier number (T0-T7), tier name, and observation tier. Use this to check how trusted an agent is before allowing it to perform sensitive actions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentIdYesUnique identifier of the agent to look up
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It clearly indicates this is a lookup operation ('Look up', 'Returns') and discloses the exact output fields: numeric score, tier number, tier name, and observation tier. This is transparent for a read-only tool, though it does not discuss authentication, staleness, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the action and resource, and every sentence adds value. The return fields and use case are included without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description fully enumerates the return values (score, tier number, tier name, observation tier) and explains the operational context. Given the simple single-parameter schema and clear sibling context, the description is complete for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% because the only parameter, agentId, is described as 'Unique identifier of the agent to look up.' The description adds no additional semantic information beyond what the schema already provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Look up an AI agent's current trust score and tier in the Vorion governance system.' It clearly distinguishes this from sibling tools by focusing on a read-only trust lookup, whereas siblings like record_signal or gate_action imply writing or enforcement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit use case: 'Use this to check how trusted an agent is before allowing it to perform sensitive actions.' This provides clear context for when to invoke the tool, though it does not mention alternatives or explicit when-not-to-use conditions, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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