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vanman2024

Multilead Open API MCP Server

by vanman2024

transfer_credits

Transfer credits between users in the Multilead platform to manage account balances for lead management and campaign activities.

Instructions

Transfer Credits

This action transfers credits from the authenticated user to a specified destination user.

Args: user_id: Source user ID (authenticated user) destination_user_id: Destination user ID to receive credits quantity: Number of credits to transfer

Returns: Transfer confirmation with updated credit balances

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYes
destination_user_idYes
quantityYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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 this is a transfer action but doesn't disclose critical behavioral traits: whether it's idempotent, requires specific permissions, has rate limits, validates credit availability, or handles errors. The mention of 'authenticated user' implies some auth need, but this is insufficient for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear title, brief purpose statement, and organized parameter/return sections. It's appropriately sized for a 3-parameter tool, though the 'Args' and 'Returns' headers are slightly redundant given the schema. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a mutation tool with 3 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers parameters and return purpose but lacks behavioral context (safety, side effects) and doesn't fully compensate for missing annotations. The output schema reduces need to explain returns.

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 explicitly lists all three parameters with brief semantics: 'user_id: Source user ID (authenticated user)', 'destination_user_id: Destination user ID to receive credits', 'quantity: Number of credits to transfer'. This adds meaningful context beyond the bare schema types, though it doesn't specify formats or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'transfers credits from the authenticated user to a specified destination user.' It specifies the verb ('transfers'), resource ('credits'), and direction (from authenticated user to destination). However, it doesn't differentiate from siblings, as no other credit-related tools exist in the sibling list.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., sufficient credits), exclusions, or related tools. The sibling list includes no obvious credit-related alternatives, but the description still lacks any usage context.

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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