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

With no annotations, the description carries the full behavioral burden, and it does disclose useful traits: matching is case-insensitive and applies to any cell, and results are capped at 50 rows. However, it says nothing about ordering, what happens when more than 50 rows match (truncation?), or the shape of the returned rows, and never states the read-only nature explicitly.

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 dense sentence with no filler, front-loading the resource and the matching rule ahead of the result cap. Every clause carries information, though the phrasing is terse enough that ordering and truncation behavior are squeezed out.

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 two-parameter, read-only search with no output schema and no annotations, the description covers matching semantics and the result cap, which is the core of what an agent needs. It leaves gaps on result ordering, truncation signaling when more than 50 rows match, and the structure of returned rows, so it is adequate but not 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%: the query parameter is self-documented, but limit is not. The description compensates by explaining both — query means matching cell text case-insensitively, and the cap of 50 corresponds to the limit parameter. It adds meaning beyond the raw types, though it omits that limit has a minimum of 1.

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 names a specific verb (search) plus the exact resource (rows of the TelescopeCompareHQ dataset) and the matching semantics (cells containing the query, case-insensitive). This is clearly a text-lookup operation, distinguishable from siblings like dataset_row (single row fetch), dataset_stats, and dataset_compare. It stops short of naming any sibling explicitly, so it lands at 4 rather than 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?

There is no when-to-use guidance and no distinction drawn against alternatives such as dataset_row, dataset_top, or dataset_columns, even though the sibling list shows several overlapping 'get rows' tools. Usage is only implicit: an agent must infer that this is the tool for free-text matching rather than keyed retrieval or aggregation.

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