fitbit_get_temperature

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

With no annotations, the description fully discloses key behaviors: recorded during sleep, needs ~3 nights for baseline, returns relative deviation not absolute, and explains the 'live' parameter effect on data source. This covers the essential behavioral traits.

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 efficiently structured: a one-sentence summary, behavioral notes, parameter docs, and return info. No extraneous text; every sentence adds value.

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 3 optional parameters and the presence of an output schema, the description covers all needed invocation details including date formats, defaults, and return field names. It is sufficiently complete for an AI agent to use the tool correctly.

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%, but the description compensates fully by documenting each parameter: start_date formats/default, end_date default, and live boolean meaning. It also explains the return structure, adding significant value beyond the raw 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 it returns 'nightly skin temperature variation in degrees Celsius from personal baseline', specifying the resource and metric. It distinguishes from sibling tools like fitbit_get_heart_rate by explicitly naming the temperature focus.

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 mentions 'useful as an illness/cycle/recovery signal', providing use-case guidance. However, it does not explicitly exclude other use cases or compare with siblings, leaving some ambiguity for when alternatives might be better.

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