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Log time on a job

kickserv_log_time_entry
Destructive

WRITE: log hours worked by an employee on a job. employee_id is the employee's id from kickserv_list_employees. Kickserv: POST /{account}/jobs/{job_number}/time_entries.xml.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoNote about the work.
mileageNoMileage driven.
billableNoWhether the time is billable.
ended_onNoWhen the work ended. A date/time string Kickserv can parse, e.g. `2026-10-02 09:30` or `10/2/2026 09:30am`.
job_numberYesJob number.
started_onYesWhen the work started, e.g. `2026-10-02 13:00` or `10/02/2026 01:00pm`.
employee_idYesThe employee's `id`.
number_of_hoursYesHours worked, e.g. 1.25.
time_entry_type_idNoTime entry type id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and the description mostly restates that with 'WRITE' plus the POST endpoint. It does not disclose what the write affects downstream (billing totals, job hours) or whether entries can be edited/deleted after creation, so it adds only modest context beyond annotations.

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 short sentences, front-loaded with the WRITE classification and the core action, with the lookup hint and endpoint following. No filler.

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?

For a 9-parameter write with no output schema and only a destructiveHint annotation, the description covers the essentials of what it does but omits side effects and defaults (e.g., billable default, time_entry_type_id optionality impact). Adequate but with clear gaps.

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 100%, so the baseline is 3, but the description adds a genuine cross-tool fact: employee_id comes from kickserv_list_employees. That is meaning the schema does not provide, which lifts it above baseline.

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?

States a specific verb and resource: 'log hours worked by an employee on a job', and prefixes it with 'WRITE'. An agent can immediately distinguish this mutation from read siblings such as kickserv_list_job_time_entries.

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?

Usage is implied by the WRITE framing and the employee_id pointer to kickserv_list_employees, but there is no explicit when-to-use/when-not guidance and no mention of alternatives (e.g., updating vs creating a time entry).

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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