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

Annotations already declare readOnly, idempotent, and closed-world, so the safety bar is low; the description still adds value by clarifying that whitespace-only lines (not just empty ones) are stripped and by stating the return value. It falls short of showing an example output, which would fully pin down the behavior.

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?

Three short lines, front-loaded with the action and followed by return and example. The example is useful but half-finished — an example output would earn the space it takes more convincingly.

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 single-parameter, non-destructive text transform with no output schema, the description covers what it does, what it returns, and a concrete input. Nothing critical is missing, though the whitespace-only edge case could be illustrated in the example.

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?

Only one parameter and schema coverage is 100%, so the schema already documents it as 'Multi-line text.' The example input conveys the expected shape (a JSON object with a 'text' key containing escaped newlines), which is a modest addition but does not go beyond the schema.

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 and resource: 'Strip blank / whitespace-only lines from the input.' The qualifier 'whitespace-only' implicitly separates it from remove_extra_spaces, but the description never names that sibling or remove_duplicate_lines, so the differentiation is left to inference.

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 implied by the purpose itself — an agent can infer this is a text-cleanup step — but there is no explicit when-to-use, no prerequisites, and no pointer to remove_extra_spaces or remove_duplicate_lines for overlapping cleanup tasks.

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