Get Price Statistics

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

Annotations already declare this as read-only, open-world, and idempotent. The description adds valuable behavioral specifics: it computes population standard deviation (not sample), includes negative/high price hours, and supports requested percentiles. The 'complete observations' phrasing also hints at a data-completeness assumption, which is useful context beyond the annotations.

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, dense sentence that front-loads the action and resource. Every listed statistic is relevant and contributes to understanding the tool's output. There is no filler or redundancy.

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 moderate complexity of a nested request object and 0% schema description coverage, the description does not fully equip an agent to correctly structure the call. The output schema and annotations cover returns and safety, but the tool's core trigger parameters (start, end, percentiles) are only vaguely alluded to. Overall, it is minimally viable but has clear gaps.

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?

With schema description coverage at 0%, the description must compensate, but it only hints at one parameter ('requested percentiles') and provides no meaning for the request object's start/end properties or how percentiles should be formatted. It does not explain that the request must contain a time interval, leaving a significant gap for an agent constructing input.

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 uses a specific verb 'Calculates' with a clear resource ('complete hourly Pool Price observations') and enumerates the exact statistics produced. This clearly distinguishes it from sibling tools like get_pool_prices or get_price_duration_curve, which focus on raw data or distribution shapes rather than aggregate statistics.

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?

No explicit guidance is given on when to prefer this tool over alternatives. The phrase 'complete hourly Pool Price observations' implies a data-completeness requirement, but it does not state when to use this versus get_price_duration_curve, find_price_events, or other statistical tools. There are no exclusions or alternative references.

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