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WYRE-AI

Time Doctor MCP Server

by WYRE-AI

timedoctor_get_worklog

Retrieve detailed Time Doctor work-session logs (start times, duration, task/project, mode) for a user or company within a specified time range. Query up to 7-day windows for best performance.

Instructions

Get detailed Time Doctor work-session log (start times, duration, task/project, mode) for a user or company within a time range. For best performance, query <=7-day windows at a time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoISO 8601 end of range (exclusive).
fromNoISO 8601 start of range (inclusive).
userNoComma-separated user IDs. Defaults to the authenticated user.
companyYesCompany ID.
taskProjectNamesNoResolve task/project names instead of only IDs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that this is a read-style operation, what data fields are included, and the performance implication of large time ranges. It does not mention pagination, response shape, permission requirements, or defaults for from/to, which would strengthen transparency.

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 deliver the purpose, scope, content, and a concrete performance tip without filler. The main action is front-loaded and the operational guidance is compact, so every sentence earns its place.

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 read-only log retrieval tool with a fully documented schema, the description covers the tool's purpose, scope, key returned fields, and the main operational concern (7-day windows). It does not explain behavior when from/to are omitted or describe the response structure, but those are minor gaps given the schema completeness and the absence of an output schema.

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?

The input schema has 100% description coverage for all five parameters, so the schema already carries the parameter semantics. The description adds only a high-level mapping between user/company/time range and the parameters, without adding new detail, so the baseline 3 is appropriate.

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 uses a specific verb and resource ('Get detailed Time Doctor work-session log') and enumerates the returned fields: start times, duration, task/project, mode. It is distinguishable from siblings like timedoctor_get_timeuse_stats by its focus on session-log details, though it does not explicitly name a differentiating sibling.

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 it clear this tool is for retrieving work-session logs within a time range for a user or company, and it adds a useful operational guideline ('query <=7-day windows at a time'). However, it does not state when not to use it or name alternatives, so the routing guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.