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Get Fraud Metrics

paybond_get_fraud_metrics
Read-only

Get tenant-wide fraud backtesting and monitoring metrics over a rolling window: flagged operators, severity counts, review outcomes, precision/false-positive rates, and backtest summary. Requires Signal analytics access.

Instructions

Use this when you need tenant-wide Signal fraud backtesting and monitoring metrics over a rolling window (flagged operators, severity counts, review outcomes, precision/false-positive rates, and backtest_summary). Requires PAYBOND_API_KEY with Signal analytics read access and the private-dashboards feature. Do not use this for one operator's fraud posture—call paybond_get_fraud_assessment instead—or for Harbor intent escrow detail—call paybond_get_intent. Idempotent read with no side effects; omit window to default to 24h; unsupported windows fail with HTTP 400 ("window must be one of 24h, 7d, or 30d").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNoRolling metrics window. Allowed values: 24h, 7d, 30d. Omit to use the gateway default 24h. Unsupported values fail with HTTP 400.
score_versionNoOptional Signal score model version to query. Omit to use the gateway default current model (1.0). Example: 1.0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNoActive metrics window label: 24h, 7d, or 30d.
tenant_idNoTenant echoed by the gateway for the authenticated API key (example: tenant-a).
window_ended_atNoRFC3339 end of the evaluated rolling window.
backtest_summaryNoHuman-readable backtest summary derived from the window metrics.
high_signal_countNoCount of high-severity fraud signals in the window.
review_open_countNoOperators currently in an open review state.
window_started_atNoRFC3339 start of the evaluated rolling window.
score_model_versionNoScore model version used for the metrics (echoes the requested score_version or the gateway default 1.0).
confirmed_risk_countNoLabeled confirmed-risk outcomes in the window.
false_positive_countNoLabeled false-positive outcomes in the window.
critical_signal_countNoCount of critical-severity fraud signals in the window.
elevated_signal_countNoCount of elevated-severity fraud signals in the window.
labeled_outcome_countNoReview outcomes labeled in the window (confirmed risk, false positive, or needs more evidence).
flagged_operator_countNoOperators with at least one fraud signal in the window.
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, but the description adds that the tool is 'Idempotent read with no side effects' and details error behavior for unsupported windows (HTTP 400). This adds useful context beyond the 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?

Three sentences, each earning its place: purpose and metrics, exclusions and alternatives, behavioral details (idempotent, defaults, error handling). Front-loaded with essential info, no fluff.

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?

For a tool with 2 optional parameters, an output schema, and no nested objects, the description covers purpose, usage, auth, error conditions, and defaults comprehensively. It is complete given the complexity.

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 description coverage is 100%, so the input schema already documents both parameters with descriptions and examples. The description adds only minor clarifications (default 24h for window, optionality of score_version). With full schema coverage, a score 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 clearly states the tool retrieves tenant-wide Signal fraud backtesting and monitoring metrics over a rolling window, listing specific metrics (flagged operators, severity counts, etc.). It distinguishes from siblings like paybond_get_fraud_assessment (single operator) and paybond_get_intent (Harbor intent escrow).

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?

Explicitly states when to use ('when you need tenant-wide Signal fraud backtesting and monitoring metrics') and when not to use, with direct references to alternative tools. Also mentions required authentication (PAYBOND_API_KEY with Signal analytics read access and private-dashboards feature).

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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