check_coverage

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

Annotations already establish readOnlyHint=true, and the description goes beyond them by disclosing the response shape ('Returns covered=true and matching datasets') despite there being no output schema. It adds no auth, rate-limit, or normalization caveats, but the returned-context disclosure is genuine added value.

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 sentences, both front-loaded: the check is stated first, the fallback path second. No filler, no repetition of the schema, and the alternative tool is named in the same breath as the failure condition.

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 read-only lookup with no output schema, the description covers purpose, return shape, and the follow-up action, which is close to complete. The one gap is that both parameters are optional and the description never says whether one, either, or both are needed to perform the check.

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, and the description's examples ('noaa', 'data.gov', 'census.gov') merely echo the schema's own examples. The description does not explain the relationship between source_url and source_name or whether one of them suffices, adding nothing beyond the structured fields.

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 gives a specific verb+resource ('check whether a known public data source ... is already on DataBazaar') and names the platform, so the agent knows exactly what question this tool answers. It does not, however, distinguish itself from other discovery siblings such as find_data_for_task or search_datasets, leaving some ambiguity about which lookup to prefer.

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?

It explicitly routes the negative case to an alternative tool ('otherwise log_data_gap can record demand'), which is real when-to-use guidance. It gives no guidance on when to prefer this over search_datasets/find_data_for_task, so the routing is only half complete.

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