rehydrate_text

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

With no annotations, the description carries the full behavioral burden. It does reveal the transformation's direction and its dependency on a prior scrub_text call, but it says nothing about side effects, whether it is a pure transformation, or what happens with unknown or malformed placeholder tokens (left as-is vs. error).

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 front-loaded sentence with the action, the token examples, and the data dependency. No filler, no redundancy with the schema.

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 two-parameter transformation with full schema coverage and no output schema, this is close to sufficient, but the lack of any statement about the return value and about handling of unmatched or unknown tokens leaves a real gap for an agent deciding how to react to unexpected results.

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 100% and both parameters are documented there, so the baseline is 3. The description adds modest value by naming the placeholder token format and clarifying that the vault is the one returned by scrub_text, but it gives no detail on key/node structure of the nested vault object.

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 ('Restore') and resource ('tokenized placeholders'), gives concrete placeholder examples, and ties the input to the vault map produced by scrub_text. This makes it trivially distinguishable from its siblings scrub_text and scrub_json, which go in the opposite direction.

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 phrase 'using the vault map returned by scrub_text' makes the prerequisite and the correct call ordering explicit, and 'in LLM responses' scopes where it applies. It stops short of stating when not to use it (e.g., raw text containing no tokens, or text not scrubbed by this vault).

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