MCP Server Framework

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 the return value ('Human-readable time difference') but lacks details on format (e.g., days, hours), error handling (e.g., for invalid inputs), or performance traits. For a calculation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves beyond basic functionality.

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, starting with the core purpose in the first sentence. The Args and Returns sections are structured efficiently, with each sentence adding clear value. There is no redundant or verbose content, making it easy for an agent to parse quickly.

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 low complexity (simple calculation), 2 parameters, and the presence of an output schema (which covers return values), the description is minimally adequate. It explains the purpose and parameters but lacks behavioral details like error cases or output examples. With no annotations, it should do more to be fully complete, but the output schema mitigates some gaps.

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 semantics beyond the input schema, which has 0% description coverage. It specifies that start_timestamp and end_timestamp are Unix timestamps, clarifying their format and purpose, which the schema only indicates as integers. With 2 parameters and low schema coverage, this compensation is effective, though it could detail units or validation rules.

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 as 'Calculate the difference between two timestamps,' which is a specific verb (calculate) and resource (time difference). It distinguishes itself from siblings like get_current_time or get_timestamp, which provide single timestamps rather than calculating differences. However, it doesn't explicitly differentiate from parse_timestamp, which might also involve time calculations, keeping it from a perfect 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. It doesn't mention scenarios like comparing dates, measuring durations, or contrast with siblings such as parse_timestamp for formatted time parsing. Without any usage context or exclusions, the agent must infer based on the purpose alone.

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