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neev-25

Smart Expense Management MCP

by neev-25

explain_settlement_algorithm

Explains the minimal debt settlement algorithm for group expenses, useful for learning and interview preparation.

Instructions

Explains how the minimal debt settlement algorithm works. Great for learning and interview preparation!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations exist, so the description carries the burden. It implies a read-only, informational tool with no side effects. This is sufficient and accurate.

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?

Two sentences front-load the purpose and add usage context. Efficient, though a touch verbose with 'Great for learning and interview preparation!' being slightly extraneous but acceptable.

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?

Given zero parameters and an output schema, the description adequately covers purpose and usage. No gaps for a simple explanatory tool.

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?

No parameters are defined, and schema coverage is 100%. The baseline score of 4 applies as described in guidelines.

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 verb 'Explains' and the resource 'how the minimal debt settlement algorithm works.' It distinguishes from sibling tools, which are transactional (e.g., add_expense, settle), by being educational.

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 adds 'Great for learning and interview preparation!' which provides clear context for when to use the tool. No exclusions or alternatives are needed given its unique nature among siblings.

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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