starlink_history

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that the tool aggregates data into min/avg/max, covers specific metrics, and is intentionally token-efficient. For a read-only history query, these are the key behavioral traits, though edge cases and exact time-window semantics are not discussed.

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 short, front-loaded with the main purpose, and adds useful details about metrics and token efficiency. There is slight redundancy between 'statistical summary' and 'aggregated stats', but overall it is lean and well structured.

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 tool with one optional parameter and an output schema, the description covers the essential invocation context: what data is returned, the aggregation approach, and the metrics involved. It lacks explicit sibling comparisons, but the tool is simple enough that this is a minor gap.

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?

The only parameter is fully documented in the schema with default, minimum, maximum, and unit ('Number of 1-second samples'). The description adds context about sample windows but does not materially expand beyond the schema, so the baseline score of 3 is appropriate.

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 a specific verb ('Get') and resource ('recent throughput/latency/power history'), and clarifies the output form ('statistical summary (min/avg/max)'). It is clear, though it does not explicitly differentiate itself from sibling tools.

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 implies a clear use case — retrieving aggregated stats over a sample window rather than raw per-second data — and mentions token efficiency. However, it does not name sibling alternatives or state explicit when-to-use/when-not-to-use conditions.

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