check_availability

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks availability but does not describe what 'available' means (e.g., prediction exists, is accessible, meets quality thresholds), the response format (e.g., boolean, status details), or any limitations (e.g., rate limits, authentication needs). For a query tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, clear sentence that efficiently conveys the core function without unnecessary details. It is front-loaded with the main action ('Check') and resource, making it easy to parse. There is no wasted verbiage, and every word contributes directly to understanding the tool's purpose.

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 lack of annotations and output schema, the description is incomplete for a query tool. It does not explain what the tool returns (e.g., availability status, error messages) or behavioral aspects like response time or failure modes. While the purpose is clear, the absence of output and behavioral details makes it inadequate for fully informed use, especially in a context with many sibling tools.

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 description coverage is 100%, with the single parameter 'uniprotId' documented as 'UniProt accession to check'. The description adds no additional meaning beyond this, such as format examples (e.g., 'P12345') or validation rules. Since the schema fully covers the parameter, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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 purpose: checking AlphaFold structure prediction availability for a UniProt ID. It specifies the verb ('check'), resource ('AlphaFold structure prediction'), and target ('UniProt ID'), making the intent unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_structure' or 'download_structure', which might retrieve or download actual structures rather than checking availability.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing a valid UniProt ID, or compare it to siblings like 'get_structure' (which might fetch the structure if available) or 'validate_structure_quality' (which might assess existing structures). Without such context, users must infer usage from the tool name alone.

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