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

With no annotations, the description bears the full burden of behavioral disclosure and pays it off: it states the exact return shape ('count per pattern class and a total, nothing else'), the no-retention/no-logging/no-echo guarantees, the 'redaction-ok' skip rule, and the 100KB input cap. This is comprehensive behavioral disclosure.

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?

Five short sentences each add a distinct fact: scope, return shape, privacy guarantee, marker behavior, and size limit. The text is front-loaded with the action and pattern list, with no filler or repetition.

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 tool with no output schema, the description is complete: it specifies inputs, limits, return values, special marker handling, and privacy semantics. An agent has everything needed to decide whether to call it and what to expect.

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 100%, so the baseline of 3 applies and the schema already documents the text parameter including the truncation behavior. The tool description adds useful context about what is scanned, but it does not add parameter-level detail beyond what the input schema 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 opens with a specific action ('Scan text for the shapes of private content') and names the exact pattern classes it detects, so an agent can identify what the tool does. It does not explicitly contrast itself with siblings such as lookup_pattern, so it stops short of full sibling differentiation.

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 phrase 'before it goes anywhere public' clearly situates the tool as a pre-publication safety check, giving a concrete when-to-use context. It does not list exclusions or name alternatives, but the intended usage is clear enough for the one-parameter tool.

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