IT Tools MCP Server

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

Annotations provide readOnlyHint=false, indicating potential mutation, but the description doesn't add behavioral details beyond this. It doesn't explain what 'calculate' entails—e.g., if it's a pure computation with no side effects, error handling, or output format. Since annotations cover basic safety, the description adds minimal context, meeting the lower bar but lacking depth.

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

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

The description is extremely concise—a single, front-loaded sentence: 'Calculate percentages, percentage of a number, or percentage change.' It wastes no words and directly states the tool's function, making it efficient and easy to parse for an AI agent.

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

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

Given the tool's moderate complexity (3 parameters, no output schema, and annotations with readOnlyHint=false), the description is adequate but incomplete. It covers the basic purpose but lacks details on output format, error cases, or when to use versus siblings. With no output schema, more context on return values would be helpful, but the description doesn't provide it.

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

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

Schema description coverage is 100%, with clear parameter descriptions and an enum for 'operation'. The description mentions 'percentage of a number' and 'percentage change', which loosely map to the enum values but don't add new semantic details beyond the schema. This aligns with the baseline score when schema coverage is high.

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

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

The description clearly states the tool's purpose: 'Calculate percentages, percentage of a number, or percentage change.' It specifies the verb ('calculate') and the resource ('percentages'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'evaluate_math' or 'convert_number_base', which could also handle mathematical operations, so it misses full sibling distinction.

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

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 sibling tools like 'evaluate_math' for general math or 'convert_number_base' for numeric conversions, nor does it specify contexts or exclusions for percentage calculations. This lack of usage context leaves the agent without clear selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.