aggregate_observations

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 'server-side' computing but doesn't disclose rate limits, required auth, result limits, or what the aggregated output structure looks like. With zero annotation coverage for a computation-heavy tool, this is a significant gap.

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 with zero waste, listing the purpose and bucket options concisely. However, this conciseness sacrifices useful detail that the tool needs — the tradeoff favors brevity over informativeness given the 9 parameters.

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?

The tool has 9 parameters, 0% schema coverage, and a complex aggregation operation, yet the description explains almost nothing about parameter interplay (interval vs operation vs metric), what statistics can be computed, or how the output schema relates. Despite having an output schema, the input side is severely under-documented for a tool this complex.

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%, and the description adds no parameter-level meaning. There are 9 parameters (3 required), including operation (default 'max'), interval, metric, data_type — none of which are explained. The description names the bucket types but never maps them to the 'interval' parameter or explains what operation/others control. The description fails to compensate for the 0% schema coverage.

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 states 'Aggregate observations server-side over daily, ten-day, monthly, or yearly buckets' — a clear verb (aggregate) + resource (observations) + bucket sizes. However, it does not distinguish itself from sibling get_observations, which likely returns raw observations; the relationship between the two is left to inference.

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 says aggregation is over various buckets but gives no guidance on when to choose this tool versus get_observations, or what 'server-side' aggregation means operationally for the agent. No explicit when/when-not guidance or alternatives are named. The aggregation vs raw distinction is implied but not stated.

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