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Log hours on a job card

job_card_log_labor

Log hours worked on a job card: who did the work, the day, the hours and the hourly rate in whole cents, with a note on what was done. The line value is hours times rate, rounded half-up to the cent, fixed the moment it is logged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cardYesThe job card id, e.g. JC-2026-0003, or the client name when only one card has it
dateYesThe day the work was done, YYYY-MM-DD. A future date is refused
noteNoWhat was done, e.g. First fix, kitchen ring main
hoursYesHours worked, to the hundredth, e.g. 7.5 or 3.25. One entry is one worker's day at most
workerYesWho did the work, e.g. Anna
rate_centsYesThe hourly rate in whole cents. 4500 is 45.00 an hour

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

The description discloses the server-side line value calculation ('hours times rate, rounded half-up to the cent, fixed the moment it is logged'), which goes beyond the annotations. However, it does not mention potential side effects, whether records are appended, or any permission or reversal details, leaving some behavioral gaps.

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 purposeful sentences: the first states what the tool does and what inputs it takes; the second clarifies the calculation and persistence behavior. No filler or redundant wording.

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 6-parameter write operation with no output schema, the description covers the main behavior, input scope, and calculation semantics. The schema fills parameter constraints. Missing explicit guidance on return values or side-effect confirmation is a minor gap given the tool's simplicity.

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. The description adds a useful formula relating hours and rate_cents, but does not significantly deepen per-parameter semantics beyond what the schema 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 opens with a specific verb and resource: 'Log hours worked on a job card', and enumerates exactly what is logged (worker, day, hours, rate, note). It is clearly distinguishable from siblings like job_card_log_material and job_card_update_status.

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 makes the use case clear—logging labor hours—but does not explicitly contrast with job_card_log_material or mention when not to use the tool. While the purpose is implied by naming and content, there are no explicit alternative routes or exclusions.

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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