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jais2402
by jais2402

List Everhour team members

everhour_list_users
Read-onlyIdempotent

List workspace team members and retrieve their Everhour user IDs, with optional name or email filter, for admin time logging.

Instructions

List the workspace's team members with their Everhour user IDs. Admin access required.

Use this to resolve a person's name to their numeric Everhour user ID, which you then pass as 'user_id' to everhour_log_time / everhour_log_time_batch to log time on their behalf (admins only).

Args:

  • query (string, optional): case-insensitive filter on name or email. Omit to list everyone.

  • response_format ('markdown' | 'json')

Returns an array of user objects: { id, name, email, role, status, ... }.

Examples:

  • "What's Gayathri's Everhour user ID?" → query='gayathri', then read .id

  • "List all team members" → no args

Error Handling:

  • 403 → the API key is not an admin key; listing all users requires admin access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional case-insensitive filter matched against each user's name or email. Omit to list everyone.
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?

Disclosures admin access requirement, return structure, error handling (403). Annotations already mark it as read-only and idempotent; description adds context beyond those.

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?

Well-structured with sections for purpose, usage, args, returns, examples, error handling. Front-loaded with main purpose. No unnecessary text.

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 details the return array structure and fields, provides examples, and covers error handling. Complete for the tool's complexity.

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?

Schema already covers both parameters with descriptions. Description provides usage examples but no new semantic info beyond what's in the schema. Baseline 3 for high schema coverage.

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?

Clearly states it lists team members and resolves names to IDs, distinguishing it from sibling list tools like list_projects. The purpose is specific and actionable.

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?

Explicitly tells when to use: to resolve a name to an Everhour user ID for logging time, with examples and mention of admin requirement. Also indicates when not to use (non-admin will get 403).

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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