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Customer Dashboard in EZ Lawn Biller

ez_lawn_biller_customer_dashboard
Read-onlyIdempotent

Customer Dashboard 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_customer_dashboard"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, and the description reinforces this with 'opens nothing by itself', which is valuable because the tool is about opening a UI screen and could otherwise be mistaken for an action. The API-availability note explains why browser automation is required. Beyond that it says nothing about the shape or length of the returned instructions.

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?

Three sentences, none purely wasteful, but the opening is convoluted ('...in the user's own EZ Lawn Biller account from ChatGPT, Claude or any AI agent'), and the key behavioral fact that it returns instructions rather than acting is delayed until the second sentence. Front-loading the return behavior would improve it.

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 full annotation coverage, the definition supplies what an agent needs: what comes back (step-by-step screen/button/field guidance), that nothing is executed, and which tools to use to carry it out. The only omission is any hint about the format or granularity of the returned steps.

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 there is nothing for the description to disambiguate; the baseline of 4 applies. The description correctly frames this as a no-argument lookup.

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 resource (Customer Dashboard in EZ Lawn Biller) and, mid-sentence, what the tool actually returns: step-by-step instructions with screens, buttons and fields. That is specific enough for an agent to know this is a how-to/guidance tool rather than an action, though the verb is buried behind an awkward opening clause and it never distinguishes itself from the similarly named ez_lawn_biller_dashboard sibling.

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 an explicit workflow: call this to get the steps, then execute them with the cotlet_browser_* tools in the user's Cloud Browser. It also clarifies that the tool itself performs nothing. It stops short of naming when not to use it or which specific sibling covers the general dashboard case.

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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