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

Goes well beyond the readOnly/idempotent/closed annotations: discloses the refusal list, the 1,000-row and 40,000-character caps, and the subtle truncation semantic that rowCount counts only materialized rows. This is exactly the behavioral context annotations cannot carry.

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?

Four dense sentences, each carrying distinct information: scope, alternative tool, refusals, and limits. The core 'what it does' is front-loaded with zero filler.

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?

With an output schema present, return values need no explanation; the description still covers safety profile, restrictions, and result-size limits, which is everything an agent needs to invoke it correctly. The truncation caveat closes the one subtle 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?

Schema coverage is 100% (baseline 3), and the description adds value by explaining the effective row cap and the 40,000-character truncation behavior tied to rowLimit, plus the read-only constraint on sql. It doesn't spell out the canvas_id token format, but the schema already does.

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?

States a specific verb and resource ('Run one read-only SELECT over tables') scoped to an explicit canvas_id, and routes to the describe sibling for name/unit inspection. An agent can distinguish this from the fetching siblings (get_timeseries, get_climatology) without opening a schema.

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 says to use nasa_power_dataframe_describe to inspect names and units before querying, giving a clear alternative for that subtask, and enumerates what is refused (external files, imports, writes, system catalogs). It does not contrast against the data-fetching siblings, so it falls short of a full when/when-not map.

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