crehq_purchased_datasets_list

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a simple purpose statement by detailing the exact returned fields: 'snapshot_as_of, hosted_access_until, whether hosted MCP querying is active, and whether the buyer still owns the file snapshot after hosted access expires.' This gives agents concrete expectations about the tool's output and decision-relevant nuances.

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 two sentences, front-loaded with the core action, and every sentence adds value. The first sentence states what the tool does; the second sentence lists the key returned fields. No filler or repetition.

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?

For a simple tool with one optional parameter and no output schema, the description is complete: it states the purpose, when to use it, and what the returned data includes. It also explains a subtle concept (owned-file vs hosted-MCP access) that helps the agent understand the tool's relevance.

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 input schema has 100% coverage for its single parameter, include_expired, including a description that explains the default and its rationale. The tool description itself does not elaborate on the parameter, but since the schema already fully documents it, a baseline score of 3 is appropriate.

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 begins with a specific verb and resource: 'List dataset snapshots purchased by the owner of the connected CREHQ self-serve key.' This clearly distinguishes it from sibling tools like crehq_datasets_list, which is a general dataset list, while this is specifically for purchased snapshots.

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 explicitly states when to use the tool: 'Use this before querying a buyer-owned dataset through MCP.' It provides clear context for the intended workflow, though it does not name alternative tools or explicitly state when not to use this tool.

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