Standard Metrics MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving 'key metrics over time' but lacks details on permissions, rate limits, data freshness, or error handling. For a tool that likely accesses sensitive financial data, this is a significant gap in transparency, though it doesn't contradict any annotations.

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 appropriately sized and front-loaded, with the core purpose stated first in a clear sentence. The additional parameter explanations are brief and directly relevant. There's no wasted text, though the structure could be slightly improved by integrating the parameter details more seamlessly.

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 complexity (financial data retrieval), lack of annotations, and no output schema, the description is moderately complete. It covers the basic purpose and parameters but misses behavioral aspects like data format, error cases, or how it differs from siblings. It's adequate as a minimum viable description but has clear gaps for effective tool use.

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?

The description adds meaningful context for both parameters beyond the input schema, which has 0% description coverage. It explains that 'company_id' is a 'unique identifier for the company' and 'months' specifies the 'number of months of historical data to include'. This clarifies the purpose and usage of each parameter, compensating well for the schema's lack of descriptions.

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: 'Get a financial summary for a company including key metrics over time.' This specifies the verb ('Get'), resource ('financial summary for a company'), and scope ('key metrics over time'). However, it doesn't explicitly differentiate from sibling tools like 'get_company_metrics' or 'get_company_performance', which may offer similar financial data, so it doesn't reach the highest score.

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. With multiple sibling tools related to company data (e.g., 'get_company_metrics', 'get_company_performance'), there's no indication of what makes this tool unique or when it should be preferred over others. The minimal context is insufficient for informed selection.

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