get_health_summary

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

No annotations are provided, so the description carries full burden. It describes what data is included but lacks behavioral details such as data freshness, rate limits, authentication requirements, or error handling. For a read operation with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core purpose ('Get an overview of all health data') and lists specific data types without waste. Every word contributes to understanding the tool's scope, making it appropriately sized and well-structured.

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 complexity (aggregating multiple data types) and lack of annotations/output schema, the description is minimally adequate. It covers what data is included but misses details like response format, data granularity, or how it differs from combining sibling tools. For a read-only tool with no structured metadata, it should provide more context.

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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, focusing on the tool's purpose instead. Baseline is 4 for zero parameters, as it avoids unnecessary repetition.

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 a specific verb ('Get') and resource ('overview of all health data'), listing key data types (VO2 max, activities, sleep, race predictions). It distinguishes from siblings by aggregating multiple data types, unlike single-focus tools like get_vo2max or get_sleep, though it doesn't explicitly contrast them.

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 implies usage for a comprehensive health summary, suggesting it's an alternative to calling multiple sibling tools individually. However, it lacks explicit guidance on when to use this vs. specific tools (e.g., if only sleep data is needed) or any prerequisites/exclusions, leaving usage context somewhat inferred.

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