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Log materials used on a job card

job_card_log_material

Log materials used on a job card: the item, the day it went in, the quantity and the unit cost in whole cents. The line value is quantity times unit cost, rounded half-up to the cent, fixed the moment it is logged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qtyYesHow many, to the thousandth, e.g. 2 or 0.5
cardYesThe job card id, e.g. JC-2026-0003, or the client name when only one card has it
dateYesThe day it went in, YYYY-MM-DD. A future date is refused
itemYesWhat went into the job, e.g. Copper pipe 15mm, or Consumer unit 10-way
noteNo
unit_cost_centsYesWhat one costs in whole cents. 1299 is 12.99

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only provide readOnlyHint=false and destructiveHint=false, which are minimally informative. The description adds meaningful behavioral detail: line value is quantity times unit cost, rounded half-up, and fixed at the moment of logging. This goes beyond the structured hints, though it does not describe response or duplicate handling.

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?

Two concise sentences with no filler. The first states the action and operands, the second defines the key calculation. The information is front-loaded and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the inputs and the core value formula, which is enough for a basic call. However, there is no output schema and no mention of side effects, response, or whether repeated logging creates duplicates. It leaves some operational questions unanswered.

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 83%, so the schema already documents most parameters. The description adds the qty × unit_cost relationship and the rounding rule, which helps, but it does not clarify the undocumented 'note' parameter. Baseline 3 is appropriate given high schema coverage.

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 names a specific verb and resource: 'Log materials used on a job card', and enumerates the captured fields. It is clearly distinct from the sibling job_card_log_labor tool, so an agent can tell them apart without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states what the tool does but gives no when-to-use guidance, exclusions, or alternatives. Since job_card_log_labor exists as a sibling, the description should have mentioned that labor logging belongs to that tool.

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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