read_workspace

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. 'Get workspace details' implies a read operation, but it doesn't specify whether this requires authentication, what format the details are returned in, potential error conditions, or any rate limits. For a tool with zero annotation coverage, this is a significant gap in behavioral context.

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 at just three words, front-loading the core purpose without any unnecessary elaboration. Every word earns its place, making it efficient for quick comprehension by 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 lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'workspace details' includes, how results are structured, or any behavioral traits like error handling. For a read operation with no structured output documentation, the description should provide more context about what the agent can expect.

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 description doesn't mention parameters at all, but the input schema has 100% description coverage with a clear 'uuid' parameter documented. Since the schema does the heavy lifting, the baseline score of 3 is appropriate—the description adds no parameter semantics beyond what's already in the structured data.

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 'Get workspace details' clearly states the verb ('Get') and resource ('workspace details'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_workspaces' or 'read_task', which would require specifying what makes this particular read operation unique.

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. With sibling tools like 'list_workspaces' available, there's no indication whether this is for retrieving specific workspace details by UUID versus listing multiple workspaces, leaving the agent to infer usage context from the parameter schema alone.

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