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by GetSensr-io

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Python

Remote

get_user_by_email

Find a user by email with exact match. Returns user object or error message.

Instructions

Find a user by email (exact match preferred).

Params:

email (str, required)

Returns: {data: user|null} or {error:...}

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "email": "<email>"
    },
    "name": "get_user_by_email"
  }
}

Input Schema

Name	Required	Description	Default
`email`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 30, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations are absent, so the description carries the full transparency burden. It discloses the return shape ({data: user|null} or {error:...}) but does not address permissions, case sensitivity, or side effects. Adequate for a simple read-only lookup.

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 extremely concise and well-structured: a one-line purpose followed by a param block and a return block. Every sentence adds value with no filler.

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 single-parameter lookup tool, the description covers purpose, parameter meaning, and return format. It is complete enough, but the output schema already covers return values, and the description misses explicit boundaries or edge cases. Overall sufficient for the tool's simplicity.

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 only provides type and required status, while the description adds the 'exact match preferred' semantic for email. This compensates for the 0% schema description coverage, though it lacks details like case-insensitivity.

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?

Clear verb 'Find' + object 'user' + method 'by email (exact match preferred)' distinguishes it from broader siblings like search_user and list_users. The purpose is unambiguous.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like search_user or list_users. The 'exact match preferred' hint implies a use case but does not state exclusions or conditions.

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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