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

Annotations already cover idempotency, destructiveness, and read-only hints. The description adds the return behavior (cleaned text plus comparison) and the pricing/access model, which are useful contextual details beyond the annotations. It does not contradict any annotation.

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 extremely concise with three sentences that front-load the core purpose, then cover output and usage guidance. Every sentence serves a distinct informative function with no redundancy or 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?

The description covers the essential context: what the tool does, the return value (comparison), when to use it (after text_scan_v1), and cost/access details. With an output schema present and a single well-described parameter, nothing important is missing.

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?

The schema already provides a full description for the only parameter 'text' (the text to clean), and the tool description repeats the same idea. Since schema coverage is 100%, the description adds no additional semantic value beyond what the schema already provides.

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 the tool removes invisible Unicode characters and replaces homoglyphs, which is a specific verb+resource action. It also mentions the before-and-after comparison output, distinguishing it from the sibling text_scan_v1 which scans rather than purges.

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 explicitly advises using this tool after text_scan_v1 to fix flagged issues, providing clear when-to-use guidance and a named alternative/sequence. This makes the usage context unambiguous and actionable.

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