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

With no annotations, the description carries the full burden and does disclose useful traits: matching is case-insensitive, it scans any cell, and results are capped at 50. It omits ordering of results, behavior when there are zero matches or when more than 50 rows match, and whether the cap truncates silently.

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 with no filler, front-loading the resource and the matching rule before the result cap. Every clause 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 two-parameter search tool with no output schema, the description says results are rows but not which columns/fields are returned, how results are ordered, or how truncation at 50 behaves. Adequate but leaves callers guessing about the response.

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 already has a schema description ('text to look for in any cell') but limit has none. The description adds the case-insensitive matching rule for query, which is real value beyond the schema, while 'up to 50' merely restates the schema's maximum.

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 states a specific verb (search) and resource (rows of the PropFirmPicker dataset) and narrows the scope to cells containing the query. It is clear enough to distinguish from dataset_columns, dataset_row, or dataset_top, though it never names those siblings explicitly.

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 explicit guidance on when to choose this tool over dataset_row, dataset_top, or dataset_compare. The substring-over-all-cells semantics imply a use case, but the agent is left to infer routing decisions from sibling names alone.

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