uniprot_get_alphafold_confidence

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

The description adds behavioral context beyond annotations: it discloses the third-party API call, provenance source, and output structure (mean pLDDT, band distribution). It also warns about trust implications. No contradictions with annotations.

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 well-structured with front-loaded main action, followed by detailed output explanation and usage context. Each sentence adds value, though the third-party note could be integrated more succinctly.

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 description covers output and trust implications well, but lacks details on error handling, rate limits, or the response_format parameter. Given the tool's simplicity, these gaps reduce completeness.

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 coverage is 0%, so description must compensate. It mentions 'accession' implicitly but does not explain its format or constraints. The 'response_format' parameter is not described at all, missing its options or purpose.

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 fetches AlphaFold-DB pLDDT confidence summary for a UniProt accession, with specific verb and resource. However, it does not explicitly distinguish from sibling tools like uniprot_resolve_alphafold, which might provide the full model.

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 explains when to use (to assess model trustworthiness) but does not mention alternatives or when not to use. It provides context but lacks explicit guidance on selection among similar tools.

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