get_patient_summary

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

No annotations are provided, so the description carries full burden. It discloses what the tool returns (variant count, chromosome distribution, sex from X heterozygosity, basic stats) and indicates it is a read operation. However, it does not explicitly state that it is non-destructive or mention any side effects, though given the output, it is likely safe.

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?

Two sentences, front-loaded with the verb and resource, and no unnecessary words. Each sentence adds value: the first defines the output, the second gives usage guidance.

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?

Given no output schema and no annotations, the description explains the return values reasonably well. It covers the key stats but omits potential error cases or prerequisites (if any). For a simple 0-parameter tool, it is fairly complete.

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 input schema has zero parameters, so the description does not need to add parameter meaning. Per guidelines, zero parameters baselines at 4, and the description provides sufficient context for the tool's operation.

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 clearly states the tool gets a high-level summary of genotype data, listing specific elements (variant count, chromosome distribution, sex determination). This distinguishes it from sibling tools like 'query_genotype' which likely provide detailed genotype data.

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 explicitly instructs 'Call this first to understand the scope of data available,' providing a clear usage context and implying it should precede other queries.

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