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montrellcruse

ServiceTitan MCP

by montrellcruse
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TypeScript
Remote

intel_daily_snapshot

Read-onlyIdempotent

Build a one-day operational snapshot for any date from ServiceTitan data: appointment progress, revenue, collections, sold-estimate value, call outcomes, and upcoming jobs.

Instructions

Build a one-day operational snapshot in the configured tenant timezone from all fetched appointment, job, invoice, payment, estimate, and call pages plus Report 163 for the next day. Returns appointment progress, daily invoiced revenue and collections, sold-estimate value, call outcomes, highlights, and at most 20 upcoming jobs; truncation and partial source failures appear in _warnings. Results are cached for 60 seconds.

Examples:

  • "How did today go?" -> date="2026-03-10"

  • "Give me yesterday's numbers" -> date="2026-03-09"

  • "What happened on Monday?" -> date="2026-03-09"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate to snapshot (YYYY-MM-DD, defaults to today)

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

A4.1/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description adds meaningful behavior beyond that: 60-second caching, configured tenant timezone, _warnings for truncation and partial source failures, and the 20-job cap. This is exactly the kind of contextual disclosure that helps an agent reason about the result.

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 front-loaded: capability, return summary, caveats, then examples, with no filler. The phrase 'plus Report 163 for the next day' is slightly awkward and could be clearer, which prevents a perfect score.

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 read-only aggregation tool with one optional parameter and an output schema, the description covers inputs, outputs, limits, failure behavior, and caching. Nothing essential is missing for an agent to invoke it correctly.

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?

The schema already documents date with format and default behavior, and schema coverage is 100%. The description adds concrete example values with natural-language equivalents, which helps an agent correctly map user intent to the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb/resource ('Build a one-day operational snapshot') and enumerates the source domains and returned metrics, so it is clearly not a tautology. It does not explicitly compare itself to sibling tools like intel_revenue_summary, but the broad multi-source scope makes its purpose identifiable.

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

Usage Guidelines3/5

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

The examples map natural-language questions to the date parameter, which implies this tool is for daily business-review questions. However, there is no explicit guidance about when to use it versus the overlapping intel_* tools or when not to use it, leaving selection partially to inference.

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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