Garmin Connect 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 of behavioral disclosure. It mentions retrieving 'energy levels throughout the day' but does not specify the format of the return data (e.g., time-series, aggregated values), any rate limits, authentication requirements, or error conditions. For a data-fetching tool 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, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action ('Get body battery energy levels') and includes essential context ('throughout the day'), making it easy to parse and understand 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 complexity of fetching daily energy data, the lack of annotations, and no output schema, the description is incomplete. It does not explain what the output looks like (e.g., JSON structure, units), potential errors, or dependencies on other tools or data sources. For a tool that likely returns detailed time-series data, this omission reduces its usefulness for an AI agent.

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 input schema has 100% description coverage, with the single parameter 'date' fully documented in the schema itself. The description does not add any meaning beyond what the schema provides, such as explaining how the date parameter affects the energy levels or detailing default behavior. However, with high schema coverage and only one parameter, a baseline score of 3 is appropriate as the schema adequately handles parameter semantics.

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 ('body battery energy levels'), and it specifies the temporal scope ('throughout the day'). However, it does not explicitly differentiate this tool from sibling tools like 'get_stress_levels' or 'get_hrv_data', which might also provide daily energy-related metrics, leaving some ambiguity about its unique role.

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 does not mention prerequisites, such as whether it requires specific device data or user permissions, nor does it suggest sibling tools for related queries like 'get_recovery_time' or 'get_training_readiness'. This lack of context makes it harder for an agent to choose appropriately among similar tools.

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