ras_results_timeseries

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

The description discloses downsampling to 'at most max_points' and the default first-location behavior, adding valuable behavioral context beyond the schema. With no annotations, the description carries full burden, but it does not clarify the exact output structure for peak/time of peak/min/mean or how errors like missing HDF are handled.

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 front-loads the core purpose and then methodically details kind-specific parameters in a single dense paragraph. While compact, the run-on structure for kinds could be easier to parse, but each sentence contributes necessary information without fluff.

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 6-parameter tool with no output schema and no annotations, the description covers parameter semantics and downsampling well, but leaves gaps about the returned data format (what exactly 'peak / time of peak / min / mean' looks like) and error behavior. This is adequate but not fully complete.

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 description significantly enriches the schema: it specifies location formats (e.g., 'River/Reach/Station' for xsec), allowed variables per kind, mesh_cell requirements, and the role of max_points. This goes well beyond the schema's short descriptions, making parameter usage unambiguous.

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 clearly states the tool returns 'One time series from a results HDF' with derived statistics like peak and mean, and enumerates the supported kinds (xsec, ref_line, ref_point, boundary, mesh_cell). This specific verb+resource phrasing distinguishes it from sibling tools such as ras_results_summary and ras_results_compare.

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?

The description explains kind-specific usage and notes 'Omit location to get the first one,' which gives practical context. However, it does not explicitly state when to choose this tool over alternatives like ras_results_summary or ras_results_compare, leaving usage implied rather than directly contrasted.

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