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 does well by explaining default behaviors (measure_id defaults to universal NCCDB measure, quantity defaults to weight_grams when measure_id is 0, diary_group defaults to 'Breakfast'), case-insensitivity for diary_group, and the relationship between parameters. However, it doesn't mention potential side effects, error conditions, or authentication requirements.

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 well-structured with clear sections: purpose statement, usage guidance, parameter explanations. Every sentence earns its place, though the parameter explanations could be slightly more concise. The information is front-loaded with the most important guidance first.

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 (7 parameters, mutation operation) and the presence of an output schema (which means return values don't need explanation), the description is quite complete. It covers purpose, prerequisites, parameter semantics, and behavioral defaults. The main gap is lack of explicit mention that this is a write/mutation operation, though this is implied by 'Add'.

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?

With 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all 7 parameters. It clarifies the purpose of each parameter, their relationships (e.g., how measure_id=0 affects quantity), default values, and format requirements (date format, case-insensitivity for diary_group). This adds significant value beyond the bare schema.

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 specific action ('Add a food entry') and resource ('to the Cronometer diary'), distinguishing it from sibling tools like 'search_foods' or 'get_food_details'. It provides a complete picture of the tool's function beyond just the name.

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 explicitly provides when-to-use guidance by referencing sibling tools ('Use search_foods to find food_id and food_source_id, then get_food_details for measure_id and weight_grams') and includes specific usage notes for CRDB/custom foods. It effectively guides the agent on prerequisites and workflow.

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