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agentgraph-co

agentgraph-trust

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verify_trust

Check an entity's trust score, tier, grade, and component breakdown on AgentGraph to assess risk before interacting with unknown agents.

Instructions

Verify an entity's trust score on AgentGraph. Returns JSON with trust_score (0.0-1.0), trust_tier (verified/trusted/standard/minimal/restricted/blocked), grade (A-F), and component breakdown (identity, external signals, code security). Read-only, no auth required. Use before interacting with unknown agents to assess risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idYesUUID of the AgentGraph entity to verify. Get this from lookup_identity or from a previous interaction. Example: '550e8400-e29b-41d4-a716-446655440000'
min_trustNoMinimum acceptable trust score threshold on a 0.0-1.0 scale. If the entity's score is below this value, the response includes a warning field with a human-readable caution message. Default: 0.3 (minimal trust). Common thresholds: 0.1 (any activity), 0.3 (basic trust), 0.6 (high trust).
Behavior5/5

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

No annotations are provided, so the description fully carries the burden. It clearly states 'Read-only, no auth required,' which are critical behavioral traits. Additionally, it details the output format (JSON with specific fields), compensating for the lack of an output schema. No contradictions.

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 three sentences, front-loaded with the core purpose, then output details, then behavioral traits and usage. Every sentence provides essential information without redundancy. It is highly efficient and well-structured.

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

Completeness4/5

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

For a simple read-only tool with two parameters and no output schema, the description is largely complete. It covers purpose, return structure, usage context, and parameter semantics. It does not mention error handling or edge cases, but for a straightforward query, this is acceptable.

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

Parameters4/5

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

The input schema has 100% coverage with descriptions for both parameters. The description adds further value by providing an example UUID for entity_id and common thresholds for min_trust (e.g., 0.1, 0.3, 0.6 with meanings). This enhances understanding beyond the schema alone.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Verify an entity's trust score on AgentGraph'. It also lists the output fields (trust_score, trust_tier, grade, component breakdown) and suggests when to use it ('before interacting with unknown agents'). However, it does not explicitly differentiate from sibling tools like check_trust_tier or get_trust_badge, missing a chance to clarify its unique role.

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 includes explicit usage guidance: 'Use before interacting with unknown agents to assess risk.' This clearly indicates when to use the tool. However, it does not provide when-not-to-use scenarios or alternative tools, which would strengthen this dimension.

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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