EZ Lawn Biller by Cotlet

Correction preview in EZ Lawn Biller

ez_lawn_biller_correction_preview

Read-onlyIdempotent

Correction preview 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_correction_preview"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4/5.0

Behavior4/5

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

The annotations already declare read-only, non-destructive, idempotent, closed-world behavior; the description adds that the tool returns procedural UI steps and opens nothing by itself. The note about the missing public API explains why browser tools are needed. It does not cover permissions, authentication, or rate limits, which are secondary for a zero-parameter preview tool.

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 and compact at three sentences, stating the purpose and next step before the API audit. The 'ChatGPT, Claude or any AI agent' phrase and the detailed API 404 note are somewhat extraneous, but they do not obscure the tool's role.

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 preview tool with no output schema, the description conveys the return shape and that execution must happen elsewhere. It does not define the scope of corrections or any account prerequisites, so it is complete enough to call but not exhaustive.

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 zero parameters, so the baseline is 4. The description correctly adds no parameter semantics and does not mislead about inputs.

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 the specific behavior: it returns step-by-step EZ Lawn Biller instructions covering screens, buttons, and fields, and explicitly does not open or perform anything itself. That distinguishes it from execution tools, though it does not explicitly contrast with the sibling ez_lawn_biller_apply_correction, so sibling differentiation is partly implicit.

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 tells the agent this is a preview/instruction tool and directs follow-up execution to cotlet_browser_* tools in the user's EZ Lawn Biller Cloud Browser. However, it does not explicitly say when to choose this over apply_correction or other preview siblings, leaving one relevant exclusion unstated.

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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