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

With no annotations, the description carries the full behavioral burden; it usefully discloses case-insensitive matching and a 50-row cap. However it omits result ordering/ranking, the default when limit is not supplied, and any permission or error behavior, so the disclosure is partial.

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?

One tight sentence with the resource, scope, and two key behavioral facts front-loaded; every clause earns its place with no filler.

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?

No output schema or annotations exist, so the description must stand alone; it explains what rows come back but not their field shape or ordering, and there is no mention of the default limit. Adequate for a simple search tool but leaves gaps an agent would want.

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 description coverage is 50% (query documented, limit not). The description compensates partially by clarifying that matching is case-insensitive (query) and that results cap at 50 (limit), but says nothing about the default limit value or the ordering of returned rows.

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 (search) and resource (rows of the Strength Standards Calc dataset), and defines the matching rule (cells containing the query, case-insensitive). It is clearly a text-search over rows, distinct from dataset_row or dataset_stats, though it never names a sibling to sharpen the contrast.

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 by the purpose: an agent can infer this is the tool for keyword lookup, but there is no explicit when-to-use, when-not, or pointer to alternatives such as dataset_top or dataset_columns for other access patterns.

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