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job-card

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

A3.9/5.0
Behavior4/5

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

The description discloses the rounding rule (half-up to cent) and that the line value is fixed at log time, which is valuable behavioral context beyond the schema. With no annotations, it carries the burden well, though it doesn't discuss side effects or permissions.

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 sentences, front-loaded with the action, and no unnecessary detail. Every phrase contributes to understanding the tool's function and calculation.

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 logging operation with no output schema, the description covers the essential behavior: what is logged and how the line value is computed. It doesn't mention success/error responses, but that's not critical given the schema covers parameters.

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 coverage is high (83%), so the baseline is 3. The description adds the line value formula (quantity times unit cost) and clarifies that unit_cost_cents is in whole cents, providing meaning beyond the schema's parameter descriptions.

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

Purpose4/5

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

The description clearly states the action (log materials) and the key fields (item, date, quantity, unit cost). It's unambiguous about the resource and purpose, but it doesn't explicitly mention the sibling tool for labor, so it doesn't fully distinguish from job_card_log_labor.

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

Usage Guidelines3/5

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

The description implies usage for materials logging, but provides no explicit guidance on when to use it vs. job_card_log_labor. There's no mention of alternatives or exclusions, relying on the tool name to convey the distinction.

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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