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

The description states the transformation behavior (normalize to current 2-field form) and the enriched result contents (G group, P group, serologic equivalent, flags). The readOnlyHint and idempotentHint annotations already cover safety, and nothing in the description contradicts them; however, error-case behavior is left unspecified.

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 that states the action, scope, and output in about 22 words. Every clause contributes and there is no filler.

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 read-only tool with a complete schema, output schema, and safety annotations, the description provides everything needed to select and call it correctly. Input constraints and output expectations are both covered.

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 schema already documents 'name' as a single HLA allele string in any nomenclature era with an explicit non-identifier exclusion. The description echoes that context but adds no parameter syntax or format details 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 names a specific verb ('Normalize'), a precise resource ('one reported HLA allele name'), and the target state ('current 2-field form, with G group, P group, serologic equivalent, and flags'). It is immediately distinct from siblings like validate_gl_string or allele_info.

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?

It gives clear selection context: this is for a single reported allele name in any nomenclature era that needs conversion, and it explicitly excludes identifiers like patient names/MRNs. It does not name alternative sibling tools, so it stops short of full when-to-use vs alternatives guidance.

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