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

Annotations already cover read-only, idempotent, non-destructive, closed-world semantics, so the description owes little there. It adds genuine value by disclosing the indexed main_id lookup mechanism (a performance trait) and, absent an output schema, previewing the return shape.

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?

Two tight sentences with the identifier and return preview front-loaded, followed immediately by the operational warning. Dense but every clause carries information; no 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 no output schema, the description usefully sketches the return contents and the lookup behavior, and annotations handle the safety profile. Minor gaps remain around pagination/limits and the exact form of the returned slice, but nothing blocking for a 2-parameter read tool.

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%, so both parameters are already documented in the schema itself. The description restates 'by main.id' and hints at the country effect ('whether a country is in the series') but adds no syntax or format detail beyond the schema, so the baseline 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 and resource ('Peek one dataset by main.id') and enumerates what the peek returns (default slice, country membership, dataId, last values). It implicitly counters the execute_sql sibling by telling the agent not to scan the data table, but it never names an alternative sibling directly, so differentiation is only partial.

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?

Provides a clear anti-pattern ('do not scan the data table yourself for discovery'), which steers the agent away from execute_sql for exploration. It does not explicitly state the positive trigger (when to prefer this over get_dataset or search_catalog), leaving that to inference.

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