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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered; the description goes further by disclosing what the payload contains (attribution, creation and expiry times, coverage, basis counts) and a deployment-dependent quirk: on a shared-canvas deployment, omission-based listing is off and only an exact name works. That is real behavioral context annotations could not convey.

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 usage constraint (read the schema before writing SQL) is front-loaded in the final sentence and the operational rule about name versus listing is clear. The first sentence is a long enumerated field list that is dense but largely informative rather than 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?

For a one-optional-parameter read tool with annotations and an output schema, the description is complete: it covers scope, argument behavior, deployment caveat, and the handoff to ilostat_dataframe_query. It spends words enumerating return fields that the output schema already defines, which is redundant rather than missing.

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 description coverage is 100% for the single name parameter, so the pattern, case-insensitivity, and omission semantics are already documented in the schema. The description restates them ('Pass name for one dataframe. Without it, every staged dataframe is listed') without adding format or syntax beyond the schema, so the baseline of 3 applies.

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 (Describe) and a precisely scoped resource (df_<id> dataframes staged by ilostat_query_indicator / ilostat_compare_geographies or registered via ilostat_dataframe_query), and enumerates what is returned. It names the producing siblings explicitly, so an agent can distinguish it from ilostat_dataframe_query or ilostat_describe_indicator 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?

Gives explicit when-to-use routing: 'Read the schema here before writing SQL for ilostat_dataframe_query.' It also states the condition that selects the name argument (one dataframe) versus omitting it (list everything), and flags the shared-canvas exception where listing is refused.

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