kimai-timelog-mcp

summarize_time

Total logged hours over a date range, grouped by project, activity, or day for reporting.

Instructions

Total the user's logged hours over a range, grouped for reporting.

Args: from_date: defaults to 7 days ago. to_date: defaults to today. group_by: 'project', 'activity' or 'day'.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "summarize_time"
  }
}

Input Schema

Name	Required	Default
`to_date`	No
`group_by`	No	project
`from_date`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 28, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosing behavior. It clearly describes a read-only aggregation operation and the defaults for date bounds, which is useful, but it does not mention date format expectations, inclusivity of range, or what happens when no entries exist.

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?

The description is compact, information-dense, and front-loaded with the core behavior before the args list. Every sentence contributes value, with no filler or repetition of the schema.

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 tool with three optional parameters and an output schema, the description covers the operation, grouping options, and date defaults, making the tool callable. The main gap is the absence of a date format convention and explicit range inclusivity, which could cause incorrect calls despite the defaults being clear.

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 description coverage is 0%, and the description compensates well by explaining all three parameters: from_date defaults to 7 days ago, to_date defaults to today, and group_by has three explicit allowed values. It does not specify the expected date string format, but the added semantics substantially exceed the bare schema.

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 uses a specific verb ('Total') and resource ('the user's logged hours') plus grouping behavior, making the aggregation purpose unmistakable. It clearly differentiates from sibling tools like list_timesheets and recent_entries, which list raw entries rather than summarize them.

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 phrase 'grouped for reporting' implies this is for summaries rather than raw entry retrieval, but it does not explicitly state when to choose this tool over list_timesheets or recent_entries. There are no exclusions or named alternatives, leaving the agent to infer usage from context.

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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