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

No annotations are provided, so the description must carry the full burden. It does not state whether the tool returns the full text with dates replaced, a list of normalized dates, or how it handles invalid or ambiguous date formats. The minimal description leaves significant ambiguity.

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 exceptionally concise at six words, with the core action and target in the front. Every word earns its place, with no filler or redundant information.

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 one-parameter tool with no output schema, this is minimally viable but incomplete. The description does not explain the return value format (e.g., modified text vs. extracted dates), which is essential for an agent to use the result correctly. It is adequate for low complexity but lacks edge-case handling.

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 schema covers 100% of parameters, and the 'text' parameter is described as 'Text containing dates'. The description adds only the normalization context, which is already implied by the tool name. Baseline 3 is appropriate since the schema does the heavy lifting.

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 'Find and normalize dates to ISO' uses a specific verb ('find and normalize') and a clear resource ('dates'), converting them to a standard format. It distinguishes itself from sibling tools like extract_emails or extract_phones by targeting dates specifically.

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 usage when text contains dates, but provides no explicit guidance on when to choose this over alternatives or any exclusions. It is adequate but under-specified relative to the sibling toolset.

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