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montrellcruse

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by montrellcruse
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TypeScript
Remote

intel_invoice_tracking

Read-onlyIdempotent

Monitor invoice email delivery for any date range and get sent/not-sent counts, send rate, and unsent breakdowns by business unit and technician.

Instructions

Track invoice email delivery for the selected date range by combining and deduplicating Reports 2281 and 2282. Returns sent and not-sent counts, send rate, invoice amount and balance impact, and unsent breakdowns by business unit and technician; an optional business-unit filter applies to both reports. Report calls may wait for per-report/client spacing, and partial source failures are returned in _warnings.

Examples:

  • "What percent of invoices were sent this week?" -> startDate="2026-03-02", endDate="2026-03-09"

  • "Which techs are not sending invoices?" -> startDate="2026-01-01", endDate="2026-03-10"

  • "Show invoice send rate for plumbing last month" -> startDate="2026-02-01", endDate="2026-03-01", businessUnitName="Plumbing"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateYesEnd date (YYYY-MM-DD)
startDateYesStart date (YYYY-MM-DD)
businessUnitIdNoFilter by business unit ID
businessUnitNameNoFilter by business unit name (resolved via cache, e.g. 'HVAC'). Alternative to businessUnitId.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {},
+  "type": "object"
+}
  2. First observedv2.5.1

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds real behavioral value: it merges and dedupes two reports, may wait for per-report/client spacing, and returns partial source failures in _warnings. This goes well beyond the structured 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 compact and well structured: purpose first, output summary second, operational caveats third, then targeted examples. No filler or repetition of schema details.

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?

With an output schema present and annotations covering safety, the description supplies everything else an agent needs: source reports, output categories, filter semantics, latency behavior, failure handling, and example invocations. Nothing essential is missing.

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?

Schema coverage is 100%, so all parameters are already documented. The description adds meaningful context by clarifying that the optional business-unit filter applies to both source reports, and the examples provide realistic values and natural-language mappings for startDate, endDate, and businessUnitName.

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 states a specific verb ('Track invoice email delivery') and resource (Reports 2281 and 2282), then lists concrete outputs such as sent/not-sent counts, send rate, and breakdowns. This clearly distinguishes it from the many sibling intel_* analytics tools.

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 first sentence and examples give clear context for when to use this tool: invoice delivery and send-rate questions over a date range, optionally filtered by business unit. It does not explicitly name alternatives or say when not to use it, so it stops short of a 5.

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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