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Customize Routes in EZ Lawn Biller

ez_lawn_biller_customize_routes
Read-onlyIdempotent

Customize Routes in the user's own EZ Lawn Biller account from ChatGPT, Claude or any AI agent. Returns how to do it in EZ Lawn Biller step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's EZ Lawn Biller Cloud Browser. EZ Lawn Biller's official API: No publicly documented EZ Lawn Biller API was found on 11 Nov 2026: ezlawnbiller.com/api, /developers and /docs returned 404, and its FAQ and manual name QuickBooks as the only integration.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ez_lawn_biller_customize_routes"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true and openWorldHint=false, and the description is consistent with them ('opens nothing by itself'). The added API-research note explains why browser automation is required, but the description does not say whether the guidance reflects account-specific state or generic product steps, nor how fresh or reliable the instructions are.

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

Conciseness3/5

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

The core workflow is front-loaded and easy to extract, but the trailing API note is long, dated ('11 Nov 2026'), and cites 404 checks on specific URLs, which consumes significant space for marginal decision value. The essential two clauses could stand alone.

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

Completeness4/5

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

For a zero-parameter, read-only guidance tool with no output schema, the description covers what comes back (step-by-step screens/buttons/fields), what it does not do, and the follow-up path. The remaining gap is scope — which route settings are covered — but nothing critical for correct invocation 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline applies. It does not introduce any phantom inputs that would confuse the agent.

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 and resource ('Customize Routes in the user's own EZ Lawn Biller account') and, importantly, clarifies the deliverable: it returns step-by-step instructions (screens, buttons, fields) rather than performing the action. What 'customize routes' actually covers is left vague, so an agent knows the domain but not the specific capabilities.

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?

It gives explicit sequencing: this tool returns instructions and 'opens nothing by itself', and the actual change must then be made with the cotlet_browser_* tools in the Cloud Browser. That is a clear when-to-use and a named follow-up mechanism, though it offers no explicit exclusions or prerequisites such as being signed in.

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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