search_features

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is fully covered elsewhere. The description adds the shape of the result (IDs, names, values, language counts), but says nothing about the 15-item default cap or how an empty/ambiguous query behaves.

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 front-loaded sentences with zero filler: the action comes first, the return payload second. Nothing could be cut without losing information.

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?

An output schema exists, so return-value detail isn't strictly needed, and the tool is simple. Still missing is any hint about result capping/pagination via limit or how the dataset parameter scopes results, which matters for a search tool that silently defaults to 15 rows.

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 67%: query and dataset are documented in-schema, while limit has no description. The description adds no parameter meaning 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 ("Search typological features by keyword") and enumerates what comes back, so the agent knows this is a discovery/lookup tool. It does not name or contrast with the sibling get_feature, which would have made it a 5.

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?

Usage is only implied: keyword search suggests use when you don't already have a feature ID. There is no explicit when-to-use, no exclusion, and no pointer to get_feature for retrieving a known ID or to list_datasets for dataset discovery.

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