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Get Fraud Assessment

paybond_get_fraud_assessment
Read-only

Retrieve fraud assessment, review state, and signals for a tenant-scoped operator DID to inform spend workflow decisions.

Instructions

Use this when you need the read-only fraud assessment and review posture for one known tenant-scoped operator DID (review state, fraud signals, and compact fraud_assessment). Example: look up operator_did=did:web:vendor.example#booker-agent (optionally score_version=1.0) before deciding whether to continue a spend workflow for that operator. Do not use this for tenant-wide fraud backtesting metrics—call paybond_get_fraud_metrics instead—or for Harbor intent escrow detail—call paybond_get_intent. Idempotent read; returns null when no assessment exists for that operator.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operator_didYesTenant-scoped operator DID to assess. Must belong to the authenticated tenant; do not invent tenant identifiers. Examples: did:web:vendor.example#booker-agent, did:key:z6MkhaXgBZDvotDkL5257faiztiGiC2QtKLGpbnnEGta2doK.
score_versionNoOptional Signal score model version to query. Omit to use the gateway default current model. Example: 1.0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tenant_idNoTenant echoed by the gateway for the authenticated API key (example: tenant-a).
operator_didNoOperator DID echoed from the assessment response (example: did:web:vendor.example#booker-agent).
fraud_assessmentNoCompact fraud assessment for the operator (level, severity, signal counts, summary). Example shape: {"level":"high","highest_severity":"high","signal_count":1,"summary":"level=high"}.
Behavior4/5

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

Annotations already indicate readOnlyHint=true. The description adds value by stating idempotency and null returns when no assessment exists, providing behavioral context beyond annotations.

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 concise (3 sentences), front-loaded with purpose, includes an example, and clearly lists exclusions. No redundant information.

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?

Given the presence of an output schema, the description adequately covers all necessary context: purpose, usage, exclusions, and a key behavioral note about null returns. Complete for a simple read operation.

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%, so baseline is 3. The description reinforces parameter usage with an example but does not add new semantic meaning beyond the schema's built-in descriptions.

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 clearly states the specific verb 'get' and resource 'fraud assessment for one tenant-scoped operator DID'. It distinguishes from siblings by explicitly naming alternatives paybond_get_fraud_metrics and paybond_get_intent.

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

Usage Guidelines5/5

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

The description provides explicit when to use ('before deciding whether to continue a spend workflow') and when not to use, with direct references to appropriate sibling tools.

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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