_mcp_anonymize_dataset_preview

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

No annotations are provided, so the description carries full burden. It suggests a write operation but does not confirm whether the original file is preserved, what patterns are used, or any side effects like file locking or access requirements.

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?

Single sentence with no redundant words. However, it omits critical details that could be included without breaking conciseness.

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?

Despite having an output schema, the description lacks details on patterns, supported file types, or how this tool fits into a workflow with siblings like scan_data_leakage_risk or generate_synthetic_dataset.

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%. The only parameter, file_path, is not described at all in the tool description. The description mentions 'dataset file' but gives no format, validation, or usage constraints.

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 states a specific verb ('sanitize') and resource ('dataset file'), and clearly distinguishes the output ('.anon copy'). It is unique among siblings, as no other tool explicitly handles dataset anonymization.

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?

No guidance on when to use this tool vs. alternatives (e.g., sanitize_logs_for_claude), nor any prerequisites or exclusions. The agent must infer context from the name alone.

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