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

With no annotations provided, the description carries full behavioral burden. It discloses case-insensitive substring matching and a 50-row cap, which are useful. It doesn't state ordering, empty-result behavior, or confirm read-only semantics, but the core operation is transparent.

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?

A single sentence that front-loads the resource and action while packing two key constraints (case-insensitive, max 50). Every word earns its place.

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 low-complexity search tool with no annotations or output schema, the description covers the main invocation semantics and result scope. It doesn't describe output fields or pagination, but the operation is simple enough that an agent can call it correctly from this text.

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 only 50%; the query parameter is described in the schema, while limit has no description. The tool description adds the case-insensitive matching detail and behaviors for limit ('up to 50'), partially compensating for the schema gap, though it doesn't fully document the limit parameter's role.

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 uses a specific verb ('search'), names the resource ('FMlane dataset'), and defines the matching semantics ('cells contain the query, case-insensitive, up to 50'). This clearly distinguishes it from siblings like dataset_stats or dataset_row, which imply different operations.

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?

The description implies when to use it: when you need rows matching a text query in any cell. However, it does not explicitly state when not to use it or name alternatives like dataset_row for exact-row retrieval or dataset_columns for schema exploration.

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