diff_anonymization

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

No annotations provided. Description mentions it returns a 'plain unified-diff string suitable for display' but does not disclose any side effects, auth needs, or limits. Adequate for a simple read-only operation.

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?

Description is concise, uses a clear docstring format with Args and Returns, and front-loads the main purpose. Every sentence adds value.

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 simple diff tool with two string parameters and an output string, the description fully explains what it does, what inputs are expected, and what format the output takes. Complete.

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 0%, so description must add meaning. It explains 'Original (pre-anonymization) text' and 'Anonymized text from anonymize_text(),' which adds valuable context 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?

The description clearly states 'Return a unified diff comparing original and anonymized text.' It specifies the verb and resource, and the tool's distinct function is obvious among siblings.

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 use after anonymize_text() by referencing 'Anonymized text from anonymize_text().' It gives clear context but does not explicitly state when not to use.

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