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

Annotations already convey non-read-only and non-destructive behavior. The description adds meaningful context: the HTTP endpoint (POST /create-space), the exact response fields, that it is a free call, and how the returned space_id should be used downstream. This goes beyond what annotations provide.

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?

Three concise sentences cover purpose, endpoint, return values, workflow, and cost. The inaccurate 'only field is name' sentence is a defect, but the description is otherwise tight and well-structured.

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 tool is simple, has an output schema, and the description covers the creation workflow and follow-up usage. It misses nothing critical, but the parameter inaccuracy prevents a perfect score.

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%, so the baseline is 3. However, the description states 'The only field is name,' which contradicts the schema that also defines an optional api_key parameter. This is actively misleading and lowers the score despite the schema being complete.

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 action: 'Create a knowledge space to group persisted documents', names the resource, gives the endpoint, and lists return values. It also references claix.space_context.ask, which helps distinguish this from sibling tools like claix.spaces.delete.

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 workflow guidance: create a space, pass the returned space_id when extracting, and query the group with claix.space_context.ask. It does not explicitly say when not to use this tool, but the intended usage context is clear.

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