mosaic_target_validation

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds value by detailing the types of evidence returned and that it includes papers with model systems and outcomes. However, it does not disclose further behavioral traits (e.g., performance, rate limits). The description is consistent with annotations, no contradiction.

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 sentences, all front-loaded with the core action. Every sentence carries specific information: the first states the main purpose, the second enumerates evidence types, and the third adds that papers are included with model systems and outcomes. No redundant or irrelevant content.

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 the tool has only one input parameter and an output schema exists (so return values are pre-defined), the description sufficiently covers what the tool does and what it returns. It could add more context about limitations (e.g., species, data sources) but is largely complete for an agent to select and invoke appropriately.

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 already provides a description for 'gene_symbol' ('Gene symbol of the target (e.g. 'EGFR', 'BRAF', 'TP53')'), which covers the parameter meaning. The tool description repeats 'drug target' but adds no new constraints or format details. Since schema coverage is high, the description adds minimal marginal semantics.

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's verb ('Get') and resource ('experimental validation evidence for a drug target'). It lists specific evidence types (genetic, in vivo, clinical, pharmacological) from literature, distinguishing it from siblings like mosaic_get_target_papers (which likely returns raw papers) and mosaic_get_target_profile (broader summary). The purpose is unambiguous and well-defined.

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?

No explicit guidance on when to use this tool versus alternatives is provided. While the description implies usage for literature-based validation evidence, it does not mention when not to use it or point to sibling tools for different needs. This lack of context leaves the agent to infer usage without support.

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