Target Disease Associations

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

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint, so the description's burden is reduced. The description adds context about returning 'the full disease landscape' but does not contradict annotations. It meets expectations without extra detail.

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 three concise sentences plus an example, with the key action front-loaded. Every sentence adds value without redundancy.

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?

The tool has an output schema (not shown), so return values are covered. The description explains what it does and gives an example. It omits mention of optional parameters (ensembl_id, limit), but the schema and their descriptions sufficiently cover them.

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 includes descriptions for all parameters, so the tool description adds minimal additional meaning beyond reinforcing the main parameter with an example. Schema descriptions cover the remaining parameters adequately.

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 explicitly states the action ('Return all diseases associated with a protein target') with a specific resource ('via Open Targets'), and the example clarifies usage. It distinguishes from sibling tools like 'get_disease_targets' which reverse the relationship.

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 indicates the tool is 'essential for target-validation and indication-expansion', providing clear use cases. It does not explicitly list when not to use, but the context and sibling names implicitly guide selection.

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