datasets_list_all_data_modelsRetrieve every data model in an organization and automatically follow pagination to return complete results without manual page handling.
List ALL data models in the organization, automatically following pagination.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v2.0.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnlyHint=true, destructiveHint=false, openWorldHint=true). The description adds useful behavioral detail beyond annotations: it automatically follows pagination and operates at organization scope, which an agent would not learn from the structured fields alone.
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?
A single, front-loaded sentence with zero waste. It puts the resource and scope first, then the pagination behavior, which is ideal for quick scanning.
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 low complexity (no parameters, output schema present, annotations covering safety), the description is complete enough. It states scope and pagination behavior, and the output schema handles return values.
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 tool takes zero parameters, so there are no parameter semantics to document. Baseline 4 is appropriate; the description does not need to compensate for missing schema detail.
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?
States a specific verb+resource ('List ALL data models') and organization scope, plus automatic pagination. It implicitly distinguishes itself from the sibling `datasets_list_data_models` via 'ALL', but does not explicitly name or contrast with that alternative.
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 word 'ALL' and 'automatically following pagination' imply usage when a complete org-wide list is needed, but there is no explicit when-to-use, when-not-to-use, or named alternative (e.g., `datasets_list_data_models`). Guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.