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Glama
Cubiczan

finance-engines-mcp

by Cubiczan

Audit vendor invoices

audit_invoices

Run anomaly detection on invoices to flag duplicate numbers, entry lag, overdue-unpaid, amount outliers, rate changes, new charge types, unexplained credits, and inconsistent tax.

Instructions

Run all anomaly rules over a set of invoices (and optional line items): duplicate numbers, entry lag, overdue-unpaid, amount outliers, unit-rate changes, new charge types, unexplained credits, and inconsistent tax. Header-level rules always run; item-level rules run only when line items are supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNoOptional line-item rows: invoice_id, name, price, quantity, line_sum, tax_percent.
todayNoISO date used as 'today' for overdue checks (default: current date).
invoicesYesInvoice rows: id, invoice_number, supplier_id, supplier_name, issue_date, create_date, required_date, sum, sum_paid, status.
overdue_daysNoDays past due before flagging an approved-but-unpaid invoice (default 10).
entry_lag_daysNoDays between issue and entry before flagging entry lag (default 14).
rate_change_pctNoPercent unit-price change to flag for a recurring item (default 5.0).
amount_outlier_multipleNoMultiple of a vendor's median to flag as an outlier (default 3.0).
min_invoices_for_baselineNoMinimum invoices per vendor before outlier logic runs (default 3).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses that header-level rules always run and item-level rules only when line items are supplied, and it explains default thresholds via parameter descriptions. However, it does not state whether the operation is read-only or if there are side effects, which would be useful but is not critical for an analysis tool.

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

Conciseness4/5

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

The description is a single focused paragraph that front-loads the core action and lists rules concisely. The conditional note about item-level rules is included efficiently without excessive length.

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

Completeness3/5

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

The description explains the tool's behavior and inputs adequately, but it does not describe the output format or return values, which is a gap given there is no output schema. The lack of any mention of result structure may leave an agent uncertain about how to interpret the tool's response.

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 baseline is 3. The description adds a small amount of extra context by clarifying the conditional behavior of item-level rules, but it does not significantly elaborate on parameter semantics beyond the schema's own 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 tool runs anomaly rules over invoices and line items, naming the specific rule categories. This distinguishes it from sibling tools like classify_ap_exceptions or normalize_invoice_number, which have different purposes.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or conditions that would select this tool over siblings. The rule list implies a use case, but no explicit direction is given.

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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