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Edit estimate in EZ Lawn Biller

ez_lawn_biller_edit_estimate
Read-onlyIdempotent

Edit estimate 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_edit_estimate"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, and the description reinforces them by stating the tool mutates nothing and only returns guidance. It goes further by naming the actual execution path (cotlet_browser_* tools) and documenting the absence of a public API with dated evidence, which an agent cannot get from annotations alone.

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 operative behavior and the 'opens nothing by itself' caveat are front-loaded in the first sentence, with the follow-up toolchain in the second. The final API note is justified context but carries low-value detail (exact URLs, 404s, a specific date) that could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only tool the description covers mechanism and safety adequately. It never explains how, with no parameters, the specific estimate is determined — presumably from conversation or browser state — which leaves a real question for an agent trying to invoke it correctly. No output schema exists, so the loose description of the returned steps is the only signal about the response.

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 input schema takes zero parameters, so there is no parameter semantics for the description to compensate for; baseline 4 applies. The description does not explain how the target estimate is identified given the parameterless schema, but that is a completeness issue rather than a parameter-documentation gap.

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 the resource (estimate) and states the actual behavior precisely: it returns step-by-step instructions for editing in EZ Lawn Biller and 'opens nothing by itself'. This usefully corrects the misleading verb in the name. It does not, however, distinguish this from near-siblings such as ez_lawn_biller_estimate_help or ez_lawn_biller_edit_estimate_job.

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?

A workflow is implied clearly enough: call this to get instructions, then perform the edit with the cotlet_browser_* tools in the EZ Lawn Biller Cloud Browser. What is missing is any when-to-use or when-not guidance relative to estimate_help or edit_estimate_job, so the agent must infer alternative routing.

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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