EZ Lawn Biller by Cotlet

Statements to print in EZ Lawn Biller

ez_lawn_biller_statements_to_print

Read-onlyIdempotent

Statements to print 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_statements_to_print"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses the return format (step-by-step instructions), confirms the tool performs no action by itself, and explains the required follow-up browser tools. The API note further justifies why browser automation is needed.

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 core behavior and follow-up workflow are front-loaded in the first two sentences, with the API note providing relevant justification rather than filler. The opening phrase is slightly awkward and the API disclaimer is somewhat dense, but nothing is seriously wasteful.

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 zero-parameter tool with no output schema, the description covers what the agent gets back (step-by-step screens/buttons/fields), what the tool does not do (no side effects), and exactly how to proceed afterward with the browser tools. 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?

The tool has zero parameters, so there is no parameter semantics to explain; a baseline of 4 is appropriate. The description does not need to compensate for missing schema detail.

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 identifies a specific outcome — printing statements in the user's EZ Lawn Biller account — and clarifies that the tool returns step-by-step instructions rather than performing the action. It does not explicitly distinguish itself from other statement-related siblings such as ez_lawn_biller_statements or ez_lawn_biller_print_all, so it falls short of a 5.

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 a clear workflow: call this tool to get screens/buttons/fields, then execute the steps with the cotlet_browser_* tools. It also states the tool opens nothing by itself. It lacks explicit when-not guidance or named sibling alternatives, keeping it below 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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