get_statistics_range

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

With no annotations, the description carries the burden. It discloses that it uses aggregated bucket data that survives the short-term retention window, indicating behavior for old data. It doesn't mention idempotency or rate limits, but the read-only nature is clear from context and sibling names.

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?

Well-structured with Args, Returns, and Examples sections. Each sentence adds value, though the description is slightly longer than minimal. The examples are particularly helpful.

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 4 parameters, no annotations, and an output schema existing, the description covers all parameter semantics, return structure, and retention behavior. Examples complete the picture, making the tool's usage fully understandable.

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 has 0% description coverage, yet the description explains all four parameters in detail: entity_id (must be statistics-tracked), start_time (ISO-8601), end_time (ISO-8601, defaults to now), and period (enum of five values). Examples further clarify usage.

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 'Get long-term aggregated statistics for an entity over a date/time range' with a specific verb and resource. It distinguishes itself from the sibling tool `get_statistics` by emphasizing the explicit date window and retention behavior.

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?

Explicitly mentions 'Same data source as get_statistics, but with an explicit window' and provides a concrete use case example ('what was my power usage from Jan 1 to Jan 31?'). Also explains that it works for older data due to retention, helping the agent choose correctly.

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