List stored scraped datasets and their supported capabilities to discover available read-only data sources and choose the right dataset.
List stored scraped datasets. Lists available read-only scraped datasets and the capabilities supported by each dataset.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It correctly states read-only, but does not elaborate on caching, update frequency, or what 'capabilities supported' means. The term 'capabilities' is vague and lacks detail.
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 with two short sentences. It front-loads the main action 'List stored scraped datasets' and adds a clarifying second sentence. No redundant or extraneous content.
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?
Without an output schema, the description should explain the return format. It mentions 'capabilities supported' but does not describe what that includes or how the data is structured. The agent is left guessing the output shape, which is insufficient for a tool with no output schema.
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?
There are no parameters, and schema description coverage is 100% trivially. The description adds no parameter meaning beyond the schema, but baseline is 3 per instructions for high coverage.
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 verb 'List' and the resource 'stored scraped datasets', and specifies 'read-only'. It distinguishes from sibling dataset-specific tools by indicating it provides an overview of available datasets. However, it could be more explicit that this is the top-level listing tool.
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 sibling tools like datasets_airbnb_search or datasets_google_map_facets. It does not mention that this tool is useful for discovering available datasets before querying specific ones, nor does it state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.