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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It reveals that the tool accesses a 'local volatile RAM-only session map' and performs replacement, but it does not mention authentication requirements, rate limits, side effects on the session map, or error handling for missing tokens. The description adds moderate transparency beyond schema fields.

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 a single sentence of 25 words with no redundant information. It is front-loaded with the core action and provides precise details efficiently. Every word earns its place.

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 (single parameter, no nested objects, has output schema), the description covers the input, process, and data source adequately. It does not describe the output schema contents or edge cases like missing tokens, but these are not critical due to the existence of an output schema. The description is sufficiently complete for an AI agent to use correctly.

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?

The input schema has 100% description coverage for the sole parameter 'text' (description: 'The AI generated response containing placeholders to restore.'). The tool description adds value by specifying the format of placeholders (e.g., [EMAIL_1], [API_KEY_1]) and the source of original data (local volatile RAM-only session map), which enhances understanding 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 the specific verb 'replaces' and identifies the resource: masked tokens like [EMAIL_1], [API_KEY_1] in the LLM's response, using original private data from a local session map. This distinguishes it from sibling tools sanitize_file and sanitize_text, which perform the inverse operation (masking).

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 the tool is used after an LLM response contains masked tokens, but it does not explicitly state when to use it versus the sibling tools, nor does it provide when-not-to-use guidance or prerequisites. The usage context is clear but not formally outlined.

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