EZ Lawn Biller by Cotlet

Export statements in EZ Lawn Biller

ez_lawn_biller_export_statements

Read-onlyIdempotent

Export statements 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_export_statements"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.2/5.0

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 critical behavior that this tool opens nothing and only returns procedural instructions, which an agent could easily misread as an actual export action. It also justifies the browser-based workflow by documenting that no public EZ Lawn Biller API exists (404s on /api, /developers, /docs) and that QuickBooks is the only named integration.

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 with what the tool does and whether it acts, then the workflow, then the API justification. The API-investigation sentence is long and dated, but it earns its place by explaining why browser tools are required rather than a direct call.

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?

With no parameters, no output schema, and rich annotations, the description covers purpose, return nature, and the follow-up workflow adequately. It does not describe what the returned steps look like or how the agent should verify success, and it leaves sibling disambiguation unresolved.

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 and there is no schema meaning for the description to supplement. Nothing in the description misrepresents the input contract.

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 names a specific verb and resource ("Export statements in the user's own EZ Lawn Biller account") and immediately clarifies the tool's real nature: it returns step-by-step instructions rather than performing the export. It does not, however, distinguish itself from the many statement/export siblings such as ez_lawn_biller_statements_to_print or ez_lawn_biller_export_customers, so an agent must still infer which statement-related tool to pick.

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 downstream guidance: after this tool, perform the export with the cotlet_browser_* tools in the Cloud Browser, which is a clear alternative to attempting a direct API call. What is missing is any when-not guidance relative to the sibling export/statement tools, so tool selection among siblings remains ambiguous.

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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