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Book an engineer onto a job

schedule_job
Idempotent

Set a job's time window and assign an engineer to it. This changes a live schedule someone will work to, so agree the engineer and the time with the user BEFORE calling. The booking goes ahead even when it clashes, because sometimes that is intended: read warnings in the result and tell the user about every one of them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoThe brand the user said the job is in, by id or name. Optional: the job's own brand is used, and naming a different one is refused.
job_idYesFrom get_job. Never guess this.
resource_idYesFrom find_resource. Never guess this.
scheduled_endYes
scheduled_startYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only say non-readOnly, idempotent, non-destructive. The description adds genuinely non-obvious behavior: the booking proceeds even on a clash because that can be intentional, and the caller must read `warnings` in the result and relay every one to the user. That override-plus-warning contract is exactly the kind of context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the action, then the confirmation precondition, then the clash/warning contract. Every sentence carries distinct operational information with no filler.

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 output schema, the description usefully explains the one return field that matters (`warnings`) and the confirmation requirement. It leaves some gaps for a mutation of a live schedule — e.g. whether an existing booking is overwritten, and any permission requirements — but the critical agent-facing behavior is covered.

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 coverage is 60%; brand/job_id/resource_id are documented ('From get_job', 'Never guess this'), but the two date-time parameters have no schema description at all. The description only gestures at them via 'time window' and 'agree the time', adding no format, timezone, or ordering guidance beyond the pattern.

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 ('Set') and resource ('a job's time window') plus a second action ('assign an engineer to it'). This is clearly distinguishable from siblings like get_schedule, get_availability, and cancel_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 an explicit precondition — agree the engineer and time with the user BEFORE calling — which is strong usage guidance for a mutating tool. It doesn't name alternative tools or exclusions, but the schema descriptions point at get_job and find_resource for the required ids, so routing context exists elsewhere.

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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