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

No annotations are present, so the description must carry the full behavioral burden. It discloses case-insensitivity and a 50-row cap, which are valuable traits. However, it does not mention ordering, read-only nature, or behavior when no matches occur. The disclosed traits are useful but not exhaustive for a tool with no annotation safety net.

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 description is a single, concise sentence that packs core behavior, case-insensitivity, and the result cap into minimal words. It is front-loaded and contains no filler. This is an ideal example of efficient, structured description.

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 simple search tool with a clear schema and no output schema, the description covers the essential behavior: searching across cells, case-insensitivity, and limit. It implies the return type ('Rows') and does not require extensive elaboration. Minor gaps like ordering or pagination are not critical for successful invocation, so the description is adequately complete.

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 50%: query has a description, limit does not. The description adds meaning by stating that rows contain the query in any cell and that results are limited to 50, which directly clarifies the purpose of both parameters. This compensates for the missing limit description and gives the agent enough context to use them correctly.

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 clearly states that it returns rows of the Hardenvo dataset whose cells contain the query, case-insensitively, up to 50 rows. This is a specific verb-resource pair (searching dataset rows) and distinguishes it from siblings like dataset_columns or dataset_row. The name and description together leave no ambiguity about the tool's function.

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 usage (search for rows matching text) but provides no explicit guidance on when to prefer this tool over alternatives like dataset_row or dataset_top. It does not mention exclusions or alternative conditions. The agent can infer usage from the name, but there is no direct routing.

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