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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered by structured data. The description adds that results carry mapping confidence, which is useful behavioral context, but says nothing about unmatched values, fallback behavior, or open-world lookup implications.

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 well-formed sentence with the action verb front-loaded and no filler. It is efficient, though it spends words on the return value that the output schema likely already conveys.

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?

With a rich annotation set, an existing output schema, and a fully documented single parameter, the description covers what is needed to call the tool. The missing piece is routing logic relative to sibling normalizers, which is a modest gap rather than a blocker.

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 the input_data parameter is fully documented in the schema with the data categories it covers. The description adds no syntax, format, or batching detail beyond that, so baseline 3 applies.

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 and resource: it maps raw HR data values to standardized List of Values entries and returns canonical values with mapping confidence. This is far more specific than the title alone. However, it never distinguishes itself from the close sibling normalize_candidate_data, so an agent cannot tell from the text which normalizer to pick.

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-to-use guidance, and no named alternative such as normalize_candidate_data. The only usage signal is the word 'Required' next to the parameter in the schema, which is contradicted by required params being zero.

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