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Tradify: Schedule appointment

tradify_schedule_appointment

Tradify: Book a job appointment on the Scheduler for staff, optionally emailing the customer a confirmation. Books a job appointment on the Scheduler for the staff you name; with no staff the appointment is unassigned. Set email_customer to send the customer a confirmation, otherwise nothing is emailed. By default you confirm each call; you can switch that off for this tool. Reaches other people: confirm with the user before each call. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYesISO 8601 with time zone.
notesNoNotes for the crew.
staffNoStaff member names. Empty: unassigned appointment.
startYesISO 8601 with time zone.
job_idYesJob ID from list_jobs.
email_customerNoSend the customer an email confirmation. Default: false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations cover readOnly=false, openWorld=true, destructive=false, and the description meaningfully adds beyond them: it discloses the customer-email side effect, the default confirm-each-call policy (and that it can be switched off), that it reaches other people, and the required Cotlet API key scope. This is exactly the auth/side-effect/permission context annotations don't carry.

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 is front-loaded, but "Book a job appointment on the Scheduler" is stated twice in the opening two sentences, and the trailing confirmation-policy/API-key sentences read as boilerplate rather than earning their place. Functional but visibly redundant.

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 non-destructive mutation tool with full schema coverage and annotations, the description covers side effects, defaults, confirmation policy, and auth needs. It omits any indication of the return value or pagination, which is a minor gap given no output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents job_id, start/end ISO format, staff default, and email_customer default. The description largely restates the same staff and email_customer semantics rather than adding syntax or format detail beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (book) and resource (job appointment on the Scheduler) with the staff scope made explicit, including the unassigned default. An agent can distinguish this write operation from siblings like tradify_list_appointments or tradify_create_job without opening any schema.

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 clear conditional guidance: set email_customer to email the customer, otherwise nothing is sent; staff omitted means unassigned; confirm with the user before each call. It does not name alternative sibling tools (e.g. list vs schedule), so it stops short of full when/when-not 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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