Restores original sensitive values into an LLM response using the local token_map to reverse masking before returning text to the user.
Restores original sensitive values into an LLM response using the local token_map.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The LLM response containing masked tokens like {{EMAIL_1}} | |
| token_map | Yes | The token map dictionary returned during masking |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It hints that the operation is local ('local token_map'), but says nothing about the security sensitivity of reinserting real PII, permission requirements, or what happens if the token_map does not match the masked tokens.
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?
A single efficient sentence with the action front-loaded and the mechanism trailing. No padding, though it is arguably too terse given the security-sensitive nature of the operation.
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 two-parameter tool with no output schema this is minimally adequate, but with zero annotation coverage and a sensitive-data operation, the description omits ordering, matching requirements between token_map and text, and any safety context.
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?
With 100% schema description coverage on both parameters, the schema already documents 'text' and 'token_map'. The description only restates that the token_map is what was 'returned during masking', adding little 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 ('restores') and resource ('original sensitive values into an LLM response') plus the mechanism ('using the local token_map'). It is clearly the inverse of scrub_mask_text, but the description never names that sibling explicitly, so the differentiation is inferred rather than stated.
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 explicit when-to-use or when-not guidance. The agent must infer that this is called after masking, with a token_map obtained from a masking step, and nothing warns about when unmasking would be inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.