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dispatch_query

Read-only

Per-technician capacity in ONE call. mode='availability' (date): booked minutes + job count per tech on that day, lightest first. mode='workload' (from_date,to_date): booked minutes + job count per tech over a range. Use this instead of looping find_jobs per tech.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoYYYY-MM-DD — required for mode=availability.
modeYesWhich capacity view.
to_dateNoYYYY-MM-DD — required for mode=workload.
from_dateNoYYYY-MM-DD — required for mode=workload.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful behavior beyond annotations: both modes return booked minutes and job count per technician, and availability mode returns results lightest first. It does not cover permissions, rate limits, or exact return shape, but the added mode-specific behavior is meaningful.

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?

The description is short, front-loaded, and wastes no words. It leads with the core purpose, then gives mode details, then closes with the explicit alternative, all in three sentences.

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?

There is no output schema, but the description still explains the returned metrics for each mode and the ordering behavior. For a read-only, two-mode capacity query, this is nearly complete; it could be improved by explicitly distinguishing itself from sibling tools such as tech_workload.

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 each parameter, including which date fields are required for each mode. The description reinforces the mode-to-parameter mapping, but it does not add format, validation, or semantic detail beyond what the schema already provides.

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?

The description states a specific resource and scope ('Per-technician capacity in ONE call') and then distinguishes the two modes by name, required date inputs, and output metrics. An agent can immediately tell this is a capacity/workload reporting tool rather than a generic query tool.

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 clear mode-selection guidance: availability uses date, workload uses from_date/to_date. It also names an alternative workflow ('instead of looping find_jobs per tech'), but it does not explicitly address when to choose this over close siblings like tech_workload or get_tech_performance.

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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