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vanman2024

Multilead Open API MCP Server

by vanman2024

change_a_password

Update user passwords in the Multilead platform. Regular users modify their own credentials; platform co-owners can reset passwords for all users within their platform.

Instructions

Change A Password

This action changes the password for a specific user. Regular users can only change their own password and platform co-owners can change the password for all users within their platform.

Args: user_id: User ID whose password to change new_password: New password to set

Returns: Confirmation of password change

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYes
new_passwordYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates the mutation nature ('changes'), authorization requirements (user vs co-owner permissions), and the expected outcome ('Confirmation of password change'). However, it doesn't mention potential side effects (e.g., session termination), rate limits, or error conditions that might be relevant for a password change operation.

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 well-structured and appropriately sized. It begins with a clear title-like statement, follows with usage context, then documents parameters and return value in labeled sections. Every sentence adds value with no redundancy or fluff.

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 mutation tool with no annotations, 0% schema coverage, but with an output schema, the description does well overall. It covers purpose, usage guidelines, parameter meanings, and return confirmation. The main gap is lack of behavioral details like security implications, error cases, or what the confirmation contains. The output schema presumably documents the return structure, reducing the need for that in the description.

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?

Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for both parameters: 'user_id: User ID whose password to change' and 'new_password: New password to set'. This adds essential context beyond the bare schema types. However, it doesn't specify password complexity requirements or user_id format constraints that would be helpful.

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 clearly states the action ('changes the password') and resource ('for a specific user'). It distinguishes this tool from sibling tools like 'send_password_reset_email' by specifying direct password modification rather than reset initiation. 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.

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Regular users can only change their own password and platform co-owners can change the password for all users within their platform.' This clearly defines when different users should use this tool based on their permissions, addressing the critical context of authorization levels.

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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