cronometer-mcp

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

No annotations are provided, so the description carries the full burden. It describes what the tool returns but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, or how it handles errors. The description doesn't contradict annotations (none exist), but it provides minimal behavioral context beyond the basic operation.

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 well-structured and front-loaded: the first sentence states the purpose, the second details the return values, the third provides usage guidance, and the last section clearly documents parameters. Every sentence earns its place with no wasted words, making it highly concise and easy to parse.

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 (2 simple parameters), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose, usage, and parameters well. However, it lacks behavioral details (e.g., auth needs, error handling), which would be beneficial since annotations are absent, preventing a perfect score.

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 0%, so the description must compensate. It does so effectively by explaining both parameters: 'start_date: Start date as YYYY-MM-DD (defaults to 7 days ago)' and 'end_date: End date as YYYY-MM-DD (defaults to today).' This adds crucial meaning beyond the schema, including format and default values, fully addressing the parameter semantics gap.

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 daily nutrition summary with macro totals per day' and specifies what it returns ('calorie, protein, carb, fat, and fiber totals for each day'). It distinguishes itself from siblings like 'get_food_log' or 'get_micronutrients' by focusing on daily summaries rather than detailed logs or micronutrients. However, it doesn't explicitly contrast with all possible siblings, so it's not a perfect 5.

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 some usage context: 'Use this for quick daily overviews and trend analysis.' This implies when to use it (for summaries/trends) but doesn't explicitly state when not to use it or name alternatives (e.g., 'get_food_log' for detailed entries). It offers basic guidance but lacks explicit exclusions or comparisons to sibling tools.

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