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maintenance-schedule

Log maintenance on an asset

maintenance_log

Log work done on an asset: the day, what was done, the cost in whole cents, who did it, and when the next service falls due -- as a date (next_due) or as an interval in days (interval_days), never both. A repair that sets no schedule takes neither. A future work date is refused.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesThe day the work was done, YYYY-MM-DD. A future date is refused
workYesWhat was done, e.g. Oil and filter change, or Annual boiler service
assetYesThe asset id, e.g. AST-2026-0003, its serial or asset tag, or its name when only one asset has it
next_dueNoThe date the next service falls due, YYYY-MM-DD. Pass either this or interval_days, not both
cost_centsNoWhat the work cost in whole cents. 12000 is 120.00. Default 0, for in-house work
technicianNoWho did the work, e.g. Anna, or Acme Heating Ltd
interval_daysNoDays after the work date the next service falls due, e.g. 90 for quarterly. Turned into a date once, at log time

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only indicate mutability and non-idempotency. The description adds concrete behavioral constraints: a future work date is refused, next_due and interval_days are mutually exclusive, and a repair with no schedule takes neither. These help the agent avoid rejected or invalid calls.

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 short, dense sentences lead with the action, summarize the recorded fields, and then state the critical exceptions. There is no filler, and parenthesized parameter names help the agent map concepts to schema fields.

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 7-parameter mutation tool with no output schema, the description plus schema are sufficient to determine required inputs, allowed values, and rejection rules. It does not explain return/confirmation behavior, but that is not necessary for correct invocation.

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?

Schema description coverage is 100%, so the baseline is 3. The description earns credit by synthesizing the scheduling parameters into a clear either/or/neither rule that no single parameter description fully expresses, and by clarifying that cost is in whole cents.

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?

Description opens with 'Log work done on an asset'—a specific verb and resource—and lists exactly what is recorded: day, work, cost, technician, and next service. This clearly separates it from sibling read/export tools like maintenance_due and maintenance_export.

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?

The operation is clearly scoped to recording maintenance work, with explicit rules about when schedule parameters should or should not be supplied. It does not explicitly name alternative sibling tools for related tasks, but the use context is unambiguous.

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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