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Get User Details

fizzy_get_user
Read-only

Fetch detailed information about a specific user, including name, email, role, and permissions, using an account slug and user ID.

Instructions

Get detailed information about a specific user including their name, email, role, and permissions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYesThe unique user identifier: a 25-character identifier, e.g., '0000000000000000000000abc'. Get available user IDs from fizzy_get_users.
account_slugYesThe account slug identifier (e.g., '123456' or '/123456'). This identifies which Fizzy account to operate on. Get available account slugs from fizzy_get_identity or fizzy_get_accounts.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral context by enumerating the response content (name, email, role, permissions). Since there is no output schema, this return-shape disclosure carries real value beyond the 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?

A single, front-loaded sentence conveys the core operation and expected data without filler. Nothing in the description is redundant.

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 simple read-only fetch by ID, the description plus fully documented schema parameters are largely sufficient. It lacks explicit alternatives and error-case behavior, but these are minor for this tool's complexity and annotation-backed safety profile.

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 description coverage is 100%, with both user_id and account_slug already documented in the input schema. The tool description itself adds no parameter-level meaning, so the high-coverage baseline of 3 applies.

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 uses a clear verb-resource pair ('Get detailed information about a specific user') and distinguishes this from the plural sibling fizzy_get_users by focusing on a single user. The expected fields (name, email, role, permissions) make the purpose unambiguous.

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

Usage Guidelines3/5

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

The phrasing 'specific user' implies this tool is for fetching a single user's details versus listing users, but it never explicitly states when to prefer it over alternatives or when not to use it. There is no named sibling or exclusion condition.

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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