get_schema_versions

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 mentions backward compatibility and performance implications, which adds useful context beyond basic functionality. However, it lacks details on error handling, rate limits, or authentication requirements, leaving gaps in behavioral understanding for a tool with no annotation support.

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 front-loaded with the core purpose in the first sentence, followed by a concise note on usage and alternatives. Every sentence adds value without redundancy, making it efficiently structured and easy to parse for an AI 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 complexity (a read operation with 3 parameters, no annotations, and no output schema), the description is partially complete. It covers purpose and usage guidelines well but lacks parameter explanations and output details. The absence of an output schema means the description should ideally hint at return values, which it doesn't, leaving gaps in contextual understanding.

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 schema description coverage is 0%, meaning none of the three parameters (subject, context, registry) are documented in the schema. The description does not explain what these parameters mean, their expected values, or how they interact (e.g., that 'subject' is required while 'context' and 'registry' are optional with defaults). This fails to compensate for the low schema coverage, resulting in a poor score.

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: 'Get all versions of a schema for a subject.' It specifies the verb ('Get') and resource ('all versions of a schema for a subject'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_schema' or 'get_schema_by_id', which prevents a perfect score.

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 explicit usage guidance: it notes that the tool is 'maintained for backward compatibility' and recommends an alternative resource ('schema://{name}/{context}/{subject}/versions') for better performance. This clearly indicates when to use this tool (for backward compatibility) and when to prefer an alternative, fulfilling the criteria for a top score.

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