get_station_history

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

With no annotations, the description carries the full burden. It discloses timezone (Yerevan local UTC+4), the measured parameters, and the hourly/recency semantics. It stops short of describing output shape, error conditions, or data availability, but the core behavior is transparent.

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?

Two sentences, each purposeful: the first states the core function and output variables, the second supplies the required upstream lookup and timezone. 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?

For a low-complexity read tool with two fully documented parameters and no output schema, the description covers the essential context: what data is returned, the time window, the timezone, and the recommended way to obtain the station code. It could mention response format, but the pollutant list and schema make it sufficient.

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 coverage is 100%, so the parameters are already documented in the schema. The description reinforces station_code and hours by mentioning 'one air-quality station' and 'last N hours,' and adds timezone context, but it does not materially extend the schema's parameter descriptions.

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 identifies the specific operation — retrieving historical hourly readings for a single air-quality station over a configurable window — and lists the measured pollutants. This clearly distinguishes it from siblings like get_air_quality (current readings) and get_air_quality_forecast (future predictions).

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?

It gives an explicit precondition and routing cue: 'Use get_air_quality first to find a station code.' It does not spell out when not to use the tool versus the forecast sibling, but the context makes the historical-vs-future distinction clear enough.

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