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jais2402
by jais2402

Get current Everhour user

everhour_get_current_user
Read-onlyIdempotent

Retrieve your Everhour user account details including ID, name, email, and role. Use this to verify your API key and discover your user ID required for other endpoints.

Instructions

Returns the Everhour user account associated with the configured EVERHOUR_API_KEY.

Use this to discover the caller's user ID, which is required by some endpoints (e.g. when listing time records for "me") and to verify the API key is valid before logging time.

Args:

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: JSON shape: { "id": number, "name": string, "email": string, "role": string, "status": string, "headline"?: string, "capacity"?: number // weekly capacity in seconds }

Examples:

  • "Who am I in Everhour?" → call with no args

  • "What is my Everhour user ID?" → call with response_format='json' and read .id

Error Handling:

  • 401 → API key missing or invalid; check EVERHOUR_API_KEY

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
response_formatNoOutput format: 'markdown' for human-readable text or 'json' for machine-readable structured datamarkdown
Behavior5/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds value by specifying the return shape, error handling (401 for invalid API key), and confirming it's a safe read operation. No contradictions.

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 well-structured with clear sections: purpose, usage guidelines, args, returns, examples, error handling. Every sentence is informative and earns its place; no wasted words.

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?

Given no output schema, the description provides a detailed JSON shape for the return value, covers error handling, provides concrete examples, and explains usage context. It is fully complete for this simple tool.

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% with a single parameter 'response_format' having enum, default, and description. The description adds meaningful examples (e.g., 'call with response_format="json" and read .id') and ties usage to real queries, exceeding just restating the schema.

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 clearly states 'Returns the Everhour user account associated with the configured EVERHOUR_API_KEY.' It specifies a specific verb and resource. However, it does not explicitly differentiate from sibling tools like everhour_list_users, though the usage guidelines imply it's for the current user.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use context: 'Use this to discover the caller's user ID, which is required by some endpoints (e.g. when listing time records for "me") and to verify the API key is valid before logging time.' This clearly guides the agent on appropriate scenarios.

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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