Scan text for personal data and secrets

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the detection algorithms used (Verhoeff for Aadhaar, Luhn for cards) and, importantly, the privacy guarantee that it 'Returns categories and counts only, never the values' – a non-obvious disclosure an agent could not derive from annotations.

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?

Two sentences, both load-bearing: the first defines scope and rigor of detection, the second defines the return contract. Nothing is repeated from the title or annotations and the most decision-relevant information (what is detected) is front-loaded.

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 read-only, single-argument scanner with a full output schema and complete annotation coverage, the description supplies everything an agent needs: target entity types, validation strictness, and the guarantee that raw values are never returned. Input limit and output format are handled by the schema.

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 100%, so both 'text' (with its 1,000,000-character limit) and 'response_format' are fully documented in the schema. The description adds nothing about either parameter, so the baseline 3 applies.

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 names a specific verb ('Detect') and resource (text) and enumerates exactly what it looks for: Aadhaar, PAN, payment cards, email, UPI IDs, Indian mobile numbers, API/private keys. That level of specificity leaves no ambiguity about what the tool does, and none of the sibling tools (eval config, cost/memory estimation, routing) overlap with it.

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 verb 'Detect ... in text' – an agent can infer it is for scanning arbitrary text for sensitive content. However, there is no explicit when-to-use guidance, no stated prerequisites or exclusions, and no named alternative, so it stays at the implied-usage level.

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