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AroFlo MCP Server and API by Cotlet

Schedule technician in AroFlo

aroflo_schedule_technician
Read-onlyIdempotent

Schedule technician in the user's own AroFlo account from ChatGPT, Claude or any AI agent. Returns how to do it in AroFlo step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's AroFlo Cloud Browser. AroFlo's official API: Yes, AroFlo has a REST API (checked 23 Oct 2026), but it is off by default and an account asks AroFlo support to enable it.

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": "aroflo_schedule_technician"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false; the description reinforces that with 'opens nothing by itself' and specifies the return content (step-by-step screens, buttons, fields). It also explains why browser tools are required by noting the official REST API is disabled by default — context an agent could not infer from structured fields. The only gap is that it doesn't state the format/length of the returned guide.

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?

The core behavior and the browser-tool handoff are front-loaded and useful. The trailing sentence about AroFlo's REST API status and its 'checked 23 Oct 2026' date is tangential trivia that doesn't help an agent decide or invoke, so it dilutes an otherwise tight definition.

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 zero-parameter, non-destructive, no-output-schema tool, the description covers what it returns, that it has no side effects, and the exact next step. That is enough for an agent to call it correctly; only the shape of the returned guidance is left unstated.

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 and the baseline of 4 applies. The schema is fully closed and additionalProperties is false, matching the description's implication that no inputs are required.

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 a specific action+resource (schedule a technician in AroFlo) and immediately clarifies that the tool returns step-by-step instructions rather than performing the action. That clarification is valuable because the name reads like a mutating action. It does not, however, distinguish itself from guide-style siblings such as cotlet_app_guide.

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 screens/buttons/fields, then carry out the action with cotlet_browser_* tools in the AroFlo Cloud Browser. That is clear when-to-use guidance plus the follow-up alternative. It stops short of saying when to prefer this over a generic guide tool or when not to use it.

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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