datasets_list_data_modelsList all data models in your organization. Set summary_only to true for a concise, token-efficient response.
List all data models in the organization. Pass summary_only=True for concise token-efficient response.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| summary_only | No |
| 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 declare this is a safe, open-world read with no destructive effect. The description adds that summary_only yields a smaller payload, which is useful return-shape context, but it omits pagination behavior and any org-scope caveats beyond 'in the organization'.
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?
Two sentences, zero filler, with the core action front-loaded before the optimization hint. Slightly under-specified rather than over-long, but structurally sound.
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?
An output schema exists, so return values needn't be explained, but the description leaves the critical ambiguity with datasets_list_all_data_models unresolved and does not cover the limit parameter. Adequate for a simple list tool but not fully self-sufficient.
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 coverage is 0%, so the description carries the burden; it explains summary_only's purpose ('concise token-efficient response') but says nothing about limit's semantics, defaults, or pagination behavior. With one of two undocumented params covered, this is partial compensation only.
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 and resource — 'List all data models in the organization' — and adds the summary_only optimization. However, it does not distinguish itself from the close sibling datasets_list_all_data_models, leaving the agent to guess which list tool to call.
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?
No when-to-use context, no prerequisites, and no routing between this tool and datasets_list_all_data_models or datasets_list_data_model_elements. The only guidance given is how to invoke a parameter, not when to select this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.