scrub_audit_risk

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

With no annotations, the description carries the full burden, but it does disclose the essential behavioral trait: this is a non-mutating analysis that produces a score rather than modifying the input. It omits anything about data handling, storage, permissions, or the shape/range of the returned score, which matters for a privacy-focused tool.

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 compact sentence with no filler, front-loading the action and ending with the returned artifact. It is appropriately sized for a single-parameter tool.

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?

There is no output schema and no annotations, so the description must say more about the 'audit score' it returns, but it does not define its scale, what the score reflects, or what other findings accompany it. For a one-parameter read tool this is adequate but leaves the response contract vague.

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% for the single 'text' parameter, so the baseline is 3. The description adds the hint that a 'document' can be passed as well as raw text, but no format, size limit, or language details 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 (audits) and a specific resource/domain (text or document for GDPR/DSGVO Art. 32 PII risks) plus the result (an audit score). It is distinguishable from the scrub_* siblings because it analyzes rather than transforms, though it never names them explicitly.

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?

There is no when-to-use guidance. It never says whether to run this before scrub_mask_text or scrub_anonymize_json, whether it is a prerequisite to masking, or any condition under which it is not appropriate. Usage is only inferable from the word 'audits'.

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