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openai-workspace-mcp

by MSPbotsAI

openai_get_project_user

Retrieve a specific project member's details using project ID and user ID. Useful for managing OpenAI workspace members.

Instructions

Get a single project member's details.

    Args:
        project_id: The project's ID (see openai_list_projects).
        user_id: The member's user ID (see openai_list_project_users).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYes
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must convey safety profile. The verb 'Get' implies a read-only operation, but the description doesn't explicitly state non-mutating behavior or mention any permissions or potential errors. For a simple read tool, this is minimally adequate but adds no extra behavioral context.

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 short and front-loaded, with a one-line purpose followed by a focused Args breakdown. Every sentence earns its place; no filler or redundancy.

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?

With an output schema present, return-value documentation is already handled. The description covers the purpose, parameter meanings, and ID sourcing via sibling tools. For a simple single-resource getter, this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description bears full param documentation burden. The Args section explains each parameter's meaning and cross-references sibling tools to show how to obtain valid values (project_id via openai_list_projects, user_id via openai_list_project_users). This adds significant semantic value beyond the bare schema.

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 states a specific verb+resource: 'Get a single project member's details.' It clearly distinguishes from sibling tools like openai_list_project_users (listing) and openai_remove_project_user (mutation). The singular 'single' clarifies scope.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (single member lookup) and points to sibling tools for obtaining valid IDs. It doesn't explicitly state when not to use it or name alternatives, but the sibling list and 'single' wording imply the contrast.

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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