cronometer-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns ('Returns all available serving sizes with their numeric IDs and gram weights'), which is valuable context beyond basic functionality. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions.

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 perfectly structured and concise with zero waste. The first sentence states the purpose, the second provides usage guidelines, the third describes return values, and the Args section documents parameters. Every sentence earns its place and information is front-loaded appropriately.

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 has an output schema (which handles return value documentation), the description provides excellent contextual completeness. It covers purpose, workflow positioning, parameter semantics, and return content overview. For a single-parameter read operation with output schema, this is comprehensive without being redundant.

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 schema description coverage is 0%, so the description must fully compensate. It provides complete parameter documentation in the Args section, explaining that 'food_source_id' comes from 'search_foods results' and is required for the operation. This adds crucial semantic meaning beyond the bare schema type information.

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 with specific verbs ('Get detailed food information including available serving measures') and distinguishes it from sibling tools by referencing search_foods and add_food_entry. It explicitly identifies the resource (food information with serving measures) and its functional role in the workflow.

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 explicit guidance on when to use this tool ('Use this after search_foods to get the measure_id needed for add_food_entry') and distinguishes it from alternatives by positioning it as a follow-up to search_foods and prerequisite for add_food_entry. It clearly establishes the tool's place in the workflow sequence.

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