mosaic_find_undruggable_targets

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

Annotations already convey read-only and idempotent behavior. The description adds valuable details: return fields (pipeline gaps, suggested modality) and the ranking formula (opportunity_score). This goes beyond what annotations provide, giving a clear behavioral picture of output and ordering.

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 concise: one sentence for purpose, one for outputs, one for ranking logic. It efficiently communicates essential information without redundancy or unnecessary detail.

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 is a read-only query with a clear output schema (though not shown), the description covers purpose, output, ranking, and use case. It could mention edge cases (e.g., empty results) or performance notes, but it is largely sufficient for confident use.

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?

Despite schema description coverage reported as 0%, the schema actually provides good descriptions for each parameter. The description adds the ranking formula, which connects parameters to scoring but does not significantly enhance parameter understanding beyond the schema. Baseline 3 is appropriate.

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 finds validated targets that are structurally hard to hit with small molecules, distinguishing it from siblings like mosaic_assess_druggability. It explicitly calls out this is the 'white-space tool for new-modality programs', reinforcing its unique purpose.

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 provides clear usage context by identifying the tool as for new-modality programs exploring undruggable targets. However, it does not explicitly state when not to use it or directly compare it to alternatives like mosaic_assess_druggability or mosaic_find_opportunities, leaving some ambiguity.

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