EZ Lawn Biller by Cotlet

Open web page in EZ Lawn Biller

ez_lawn_biller_open_web_page

Read-onlyIdempotent

Open web page 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_open_web_page"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Beyond the read-only and non-destructive annotations, it discloses that invocation itself opens nothing, describes the step-by-step output, and identifies the separate Cloud Browser dependency. The API research supplies background but does not clarify sign-in requirements or whether the returned instructions are static or account-specific.

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 critical non-action disclosure and browser handoff appear early, but the first sentence largely restates the title with unnecessary AI-client marketing. The dated enumeration of 404 endpoints and QuickBooks integration is disproportionate and could be reduced to a brief no-public-API rationale.

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 parameterless read-only tool without an output schema, it adequately describes the returned guidance, lack of direct action, and required follow-up mechanism. It remains incomplete about the exact destination or workflow and any authentication prerequisite, so it is not fully self-contained.

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?

There are no input parameters, so the baseline score of 4 applies and no parameter documentation is necessary. The description instead usefully explains the result and subsequent tool dependency.

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?

It identifies the resource as web access in the user's own EZ Lawn Biller account and corrects the title's implication by stating that the tool returns UI steps rather than opening anything. The browser handoff distinguishes it from execution tools, but the exact page or navigation workflow covered remains unspecified.

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

Usage Guidelines5/5

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

It explicitly warns the agent not to expect this tool to open anything and directs it to use cotlet_browser_* tools afterward to perform the steps in the Cloud Browser. This establishes both the instruction-only use case and the alternative for actual execution.

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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