fitbit_trends

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

No annotations provided, so description carries full burden. It discloses auto-syncing behavior if cache is stale, and details the output format for each data type. It does not mention authentication or rate limits, but given the read-only, analytical nature, the disclosures are adequate.

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?

Description is well-structured with sections for purpose, arguments, and return values. It is comprehensive but not overly verbose. A few sentences could be tightened, but overall it is efficient and front-loaded.

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 no annotations and an output schema present, the description covers the tool's behavior (auto-sync, aggregated output), parameter details, and return format per data type. It lacks nothing essential for understanding how and when to use the tool.

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 description provides all parameter meaning. It explains each parameter: data_type lists all options, period lists options, start_date/end_date specify format and defaults, and compare describes format and override behavior. 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?

Description clearly states the tool analyses trends in cached Fitbit data, computing averages and totals, and explicitly distinguishes from raw data retrieval tools by name (fitbit_get_*). The verb 'analyse' and resource 'trends' are specific and unambiguous.

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?

Description explicitly states when to use (for aggregated trends, not raw data) and when not to use ('Not for raw data - use fitbit_get_* tools instead'). It does not provide exhaustive comparative guidance among the many trend-related siblings but clearly delineates the key distinction.

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