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Daily schedule in EZ Lawn Biller

ez_lawn_biller_daily_schedule
Read-onlyIdempotent

Daily schedule 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_daily_schedule"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The description explicitly states the tool 'opens nothing by itself', which corroborates the readOnlyHint/openWorldHint annotations and warns the agent not to expect side effects. It also adds genuinely non-schema context — that no public EZ Lawn Biller API exists, explaining why a Cloud Browser is required — though it says nothing about the shape or granularity of the returned steps.

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?

It is front-loaded with what the tool returns and then the follow-up action, which is the right order. The closing API-provenance sentence is longer than strictly necessary but does earn its place by justifying the browser-based path.

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 input parameters and no output schema, the description carries the burden well: it explains what is returned (step-by-step screens, buttons, fields), that nothing is opened, and what comes next. The only real gap is differentiation from the other schedule-reading siblings.

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 no parameter semantics are needed and the baseline applies. The schema confirms an empty object with additionalProperties false, matching the description's account-agnostic framing.

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 makes clear this is a guidance tool that 'returns how to do it in EZ Lawn Biller step by step (screens, buttons, fields)' for the daily schedule, which usefully corrects the misleading name. However, it never distinguishes itself from closely named siblings such as ez_lawn_biller_schedule, ez_lawn_biller_today_s_schedule or ez_lawn_biller_work_schedule, so an agent cannot route confidently on the name alone.

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?

There is a clear follow-up instruction ('then do it with the cotlet_browser_* tools in the user's EZ Lawn Biller Cloud Browser') that tells the agent what to do after calling. But there is no when-to-use versus when-not-to-use guidance relative to the many other schedule-related siblings.

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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