Phenotype to Protein Structures

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

Annotations indicate readOnlyHint, openWorldHint, idempotentHint. Description adds behavioral context: pipeline steps, resolution from phenotype to diseases to targets, and that it returns UniProt IDs for AlphaFold retrieval. Consistent with annotations. Could mention potential time/network dependency but not required.

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?

Reasonably concise with bullet points and an example. No wasted sentences, but could be slightly tightened (e.g., combine first two lines). Still very usable.

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's complexity (multi-step pipeline, three parameters, output schema exists), the description explains the complete workflow, provides an example, and references a follow-up tool. Output details are covered by output schema. No gaps.

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 descriptions already cover all parameters (hpo_id format, disease_limit and targets_per_disease ranges). Description adds value by showing how parameters fit into the pipeline and provides a concrete example, making the interaction understandable beyond raw 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?

Clearly states the tool maps a clinical phenotype to protein structures of disease targets. The pipeline explanation (HPO → diseases → targets → UniProt IDs) makes the specific verb and resource unambiguous. Distinguished from siblings by its multi-step mapping nature.

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?

Provides an example and mentions using the returned UniProt IDs with analyze_structural_confidence, but does not explicitly state when to use this tool versus alternatives like lookup_disease or get_disease_targets. No when-not-to-use guidance for the many sibling tools.

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