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Service catalog in EZ Lawn Biller

ez_lawn_biller_service_catalog
Read-onlyIdempotent

Service catalog 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_service_catalog"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the 'opens nothing by itself' statement largely restates structured data. The genuinely additive content is the disclosure that the return value is procedural guidance rather than account data, plus the note that no public API exists (404s on /api, /developers, /docs; QuickBooks is the only named integration), which explains why browser automation is required.

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 capability statement and the no-side-effect constraint are front-loaded, and the middle sentence routes to cotlet_browser_*. The closing API-research sentence is long and reads like provenance documentation, but it does justify the browser fallback, so it mostly earns its space.

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 parameterless, action-free guidance tool with no output schema, the description tells the agent what comes back (step-by-step screens, buttons, fields) and what to do next, which is the minimum an agent needs. The remaining ambiguity is terminological: 'service catalog' could be read as a data listing, and only the second sentence corrects that impression.

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; baseline applies. The description does direct usage toward the sibling browser tools without implying arguments this tool accepts.

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 a concrete outcome: it returns step-by-step instructions (screens, buttons, fields) for doing something in EZ Lawn Biller, and explicitly says it performs no action itself. That distinguishes it in kind from the mutating service siblings (add_service_type, edit_service_type, etc.), though it never names a specific sibling or clarifies how it differs from the similarly named ez_lawn_biller_catalog or the other service_* read tools.

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 a clear workflow rule: read the steps here, then perform the action with cotlet_browser_* tools in the Cloud Browser. What it lacks is an explicit trigger ('call this before any EZ Lawn Biller operation') and any when-not guidance, so the agent must infer the sequencing from a single sentence.

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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