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fortytimer-mcp

fortytimer-mcp

Official
by fortytimer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Flextime balance

fortytimer_get_overtime_balance
Read-only

Retrieve a user's flextime/overtime balance as of a specific date, defaulting to yesterday. Returns exact signed hours:minutes balance for quick attendance tracking.

Instructions

Flextime balance (Gleitzeit/overtime account) of a user as of a given date. Defaults to yesterday – the same figure shown on the fortyTimer dashboard. The response contains the exact balance as a signed hours:minutes string (formatted).

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": "fortytimer_get_overtime_balance"
  }
}

Input Schema

NameRequiredDescriptionDefault
as_ofNoAs-of date in YYYY-MM-DD format
user_idNoUser ID (from fortytimer_list_users). Omitted: the token owner. Visibility is enforced server-side (admin: all users, supervisor: own approver groups, employee: self only).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds relevant behavioral details: the default as-of date is yesterday, the value matches the dashboard, and the response contains a signed hours:minutes string. No contradictions with 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?

Three short sentences with no filler: purpose, default behavior, and response format. The most important scoping information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description compensates by stating the response contains the exact balance as a signed hours:minutes string. Parameter behavior is fully covered by the input schema, including visibility rules and defaults. For a simple read-only balance query, this is complete.

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?

The input schema has 100% coverage, so the baseline is 3. The description adds meaning for as_of by stating it defaults to yesterday, and for user_id by framing it as 'of a user' while the schema already documents visibility and defaulting to the token owner.

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 clearly identifies the resource as 'Flextime balance (Gleitzeit/overtime account) of a user as of a given date' and uses a specific verb 'get' via the tool name. It also distinguishes itself from sibling fortytimer_get_vacation_balance by naming the overtime account and referencing the dashboard figure.

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

Usage Guidelines4/5

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

The description implicitly tells when to use this tool: to retrieve the flextime/overtime balance as of a date, with yesterday as the default matching the dashboard. It does not explicitly name alternatives or exclusion cases, but the resource is clearly scoped enough for an agent to select it appropriately.

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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