get_point_timeseries

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

With no annotations, the description fully discloses key behaviors: default coordinates, auto-bbox expansion for area averaging, automatic splitting of periods over 100 days, ignoring dates for static data, and returning null for cloud gaps without interpolation. This is comprehensive and 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?

The description is front-loaded with the main purpose, followed by bullet points that cover key details concisely. Each point adds value, though a few could be slightly tighter. Overall it is efficient 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?

The description covers input defaults, date handling, automatic behaviors, and edge cases like static data and cloud gaps. However, it does not specify the exact structure of the output (e.g., format of basic statistics or the array), which would be helpful given no output schema. Still, it is largely complete for a tool of moderate complexity.

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?

Given 0% schema description coverage, the description adds significant meaning: lat/lon defaults, date format YYYY-MM-DD (applies to start_date/end_date), and behaviors like bbox auto-expansion (though bbox is not a parameter). It does not explicitly explain dataset_id or the output statistics, but it compensates well for the schema gap.

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 the tool returns time series (date-value array + basic statistics) for a point location, with specific examples like default coordinates and date format. It is easily distinguishable from siblings such as get_area_image which focuses on area imagery, get_dataset_info for metadata, and list_datasets for listing datasets.

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?

Description provides usage context like default lat/lon, date format, automatic bbox expansion and period splitting, and handling of static data. However, it does not explicitly mention when to use this tool over alternatives or when not to use it, though the sibling tools cover different functionalities.

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