EZ Lawn Biller by Cotlet

Apply correction in EZ Lawn Biller

ez_lawn_biller_apply_correction

Read-onlyIdempotent

Apply correction 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_apply_correction"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Strong disclosure beyond the annotations: it explicitly says it 'opens nothing by itself', so the agent knows no remote mutation occurs despite the 'apply' verb, and the note that no public EZ Lawn Biller API exists (404 on /api, /developers, /docs; QuickBooks-only integration) justifies why browser tools are required. Missing only detail on the shape/length of the returned instructions or any auth prerequisites for the Cloud Browser.

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?

Front-loads the key fact (returns instructions, opens nothing) before the API caveat, and every sentence is functional. The API-provenance paragraph is somewhat long for the value it adds to an invocation decision, keeping it short of a 5.

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 advisory tool there is no output schema, so the description must carry the return semantics; it does so only briefly ('step by step (screens, buttons, fields)') without saying how complete or ordered the guidance is. Combined with the unstated scope of what counts as a correction, an agent has enough to call it but not full confidence about what comes back.

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 no parameters (empty object, additionalProperties false, 100% coverage), so there is no parameter semantics to explain and the baseline of 4 applies. The description could have noted that the correction context must be conveyed in conversation, but no schema gap exists.

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?

States a specific verb and resource and, crucially, clarifies that the tool only returns step-by-step instructions (screens, buttons, fields) rather than performing the correction. What is less clear is what a 'correction' covers in EZ Lawn Biller (a bill, an invoice, hours, a customer record), so an agent still has to infer scope from the sibling catalog.

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?

Gives a clear two-step usage pattern: call this to get instructions, then execute with the cotlet_browser_* tools in the Cloud Browser. It does not name alternatives such as ez_lawn_biller_correction_preview or explain when a correction is appropriate versus a draft-to-live apply, which would have made it a 5.

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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