Metis · Data Guardian — Diff Anonymization

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns a 'plain unified-diff string suitable for display,' but does not discuss side effects, permissions, or safety. The behavior is simple and non-destructive, but more detail would improve transparency.

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 a single-sentence summary followed by terse parameter definitions. Every sentence adds value, and the structure front-loads the core purpose. No wasted words.

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?

Given the tool's simplicity and the presence of an output schema, the description adequately covers inputs and return type. It specifies the return is a unified-diff string for display. Minor gaps exist in error handling, but overall complete for the task.

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 0%, and the description adds brief clarifications: 'Original (pre-anonymization) text' and 'Anonymized text from anonymize_text().' This adds some meaning beyond the schema, but lacks details on constraints or formatting expectations.

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 explicitly states 'Return a unified diff comparing original and anonymized text,' which clearly identifies the verb (Return) and resource (unified diff). It distinguishes itself from the sibling 'anonymize_text' by focusing on the comparison output.

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 implies usage after anonymize_text by referencing 'anonymized text from anonymize_text().' This gives clear context for when to use the tool, though it does not explicitly state when not to use or list alternatives.

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