EZ Lawn Biller by Cotlet

Schedule in EZ Lawn Biller

ez_lawn_biller_schedule

Read-onlyIdempotent

Schedule 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_schedule"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description discloses the crucial trait that the tool performs no side effects ('opens nothing by itself') and that it emits step-by-step UI instructions rather than data. The API-availability note explains why the browser handoff is needed, which is meaningful behavioral context an agent could not infer from annotations.

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 essential point (returns instructions, no side effects, follow with cotlet_browser_* tools) is present, but it is buried after a misleading lead clause. The API-research paragraph with dates and per-URL 404 results is verbose justification rather than operational information an agent needs before calling.

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, instruction-emitting tool with annotations covering safety and no output schema, the description tells the agent what it will get back (screens, buttons, fields) and what to do next. Only the concrete output shape and any limits (e.g., does it cover all scheduling flows) are left unspecified, which is a minor gap.

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 the baseline is 4; there is nothing for the description to disambiguate. The description adds no misleading parameter expectations.

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

Purpose3/5

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

The opening sentence 'Schedule in the user's own EZ Lawn Biller account' reads like the tool performs scheduling, and only the second clause clarifies it actually 'Returns how to do it in EZ Lawn Biller step by step (screens, buttons, fields) and opens nothing by itself'. The return behavior is stated specifically, but the verb/action framing is ambiguous and nothing distinguishes this from the many sibling schedule tools (daily_schedule, work_schedule, schedule_jobs).

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?

It gives a follow-on workflow ('then do it with the cotlet_browser_* tools in the user's EZ Lawn Biller Cloud Browser') and implies it is a prerequisite for browser-driven scheduling, which is real guidance. However there is no explicit when-to-use versus the other schedule-related siblings, and no statement of when this tool should not be called.

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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