get_protein_structure

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

No annotations are provided, so the description carries the burden. It discloses that the tool fetches metadata and pLDDT scores, implying a read-only operation, but does not mention error behavior, prerequisites, or any side effects. It adds some behavioral context but lacks depth.

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 extremely concise: one purpose sentence and one annotated parameter block. No filler or redundant content, making it easily scannable for an agent.

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 simplicity (single parameter), the presence of an output schema, and the clear purpose statement, the description is complete. It does not need to describe return values since the output schema likely covers that, and the input is fully specified.

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 0% description coverage, but the description compensates with an 'Args' section that explains uniprot_id as a UniProt accession ID and provides a concrete example ('P00533' for EGFR). This fully clarifies the parameter's meaning and format.

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 function with a specific verb and resource: 'Fetch AlphaFold 3D protein structure metadata and pLDDT confidence scores.' This is distinct from sibling tools like search_literature or get_gene_info, as it focuses on structure 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 implies usage when protein structure data is needed, but does not explicitly state when to use this tool over alternatives or mention any exclusions. It provides no guidance on complementary or alternative tools, so usage context is only implied.

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