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enzoemir1

invoiceflow-mcp

Assess Payment Risk

invoice_risk
Read-onlyIdempotent

Assess an invoice's late-payment risk (0-100) by analyzing amount, client history, due date, and reminders to prioritize collections.

Instructions

Predict late-payment risk for a specific invoice on a 0-100 scale. The model combines invoice amount (relative to client average), client payment history (avg_days_to_payment, late_payment_count), days remaining until due date, and prior reminder_count. Returns {risk_score (0-100), risk_level ("low"|"medium"|"high"|"critical"), factors (array of {factor, impact, detail}), recommended_action (string), next_reminder_date (ISO string or null)}. Use for prioritizing collection effort on high-value invoices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
invoice_idYesUUID of the invoice to assess
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint true, indicating safe, non-destructive behavior. The description adds value by explaining the model inputs (invoice amount, client history, etc.) and output structure (risk score, factors, recommended action), which goes 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 three sentences, front-loaded with the core purpose, and each sentence adds value: purpose, model inputs, output and use case. No wasted words.

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 tool's simplicity (one param, no output schema), the description fully covers purpose, behavioral model, return values, and usage context, making it complete for agent selection and invocation.

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% for the single parameter 'invoice_id', and the schema already describes it as a UUID. The description only says 'for a specific invoice', adding no additional meaning beyond the schema, so baseline score applies.

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 predicts late-payment risk for a specific invoice on a 0-100 scale, using a specific verb and resource. It also mentions the use case (prioritizing collection effort), distinguishing it from sibling tools like invoice_list or cashflow_report.

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 explicitly says to use for prioritizing collection effort on high-value invoices, providing clear context. However, it does not mention when not to use the tool or suggest alternatives, leaving a minor gap.

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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