get_user_by_email
Retrieve user details from TestRail using an email address to identify and access specific user information.
Instructions
Get a user by email address
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address |
Retrieve user details from TestRail using an email address to identify and access specific user information.
Get a user by email address
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool's function but doesn't disclose behavioral traits like whether it's read-only (implied by 'Get'), what happens if the email isn't found (returns null/error), authentication needs, rate limits, or response format. For a lookup tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple lookup tool. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no output schema, no annotations), the description is minimally adequate but lacks completeness. It doesn't cover behavioral aspects like error handling or response format, which are important for a lookup tool. With no annotations or output schema, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'email' fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., email format, validation rules). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and target resource ('a user'), specifying the lookup method ('by email address'). It distinguishes from sibling 'get_user' (which likely uses ID) and 'get_users' (which lists multiple users), but doesn't explicitly mention these alternatives. The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need to find a user by email rather than ID), but doesn't explicitly state when to use this vs 'get_user' or 'get_users'. No guidance on prerequisites, error conditions, or alternatives is provided. Usage is clear from the name but not elaborated.
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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