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pools_create

Create a new Databricks instance pool with specified node type, idle instances, and auto-termination settings.

Instructions

Create a new instance pool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_pool_nameYesPool name
node_type_idNoNode type ID (mutually exclusive with instance_pool_type)
min_idle_instancesNo
max_capacityNo
idle_instance_autotermination_minutesNo0 disables idle termination
enable_elastic_diskNo
disk_specNo
preloaded_spark_versionsNo
preloaded_docker_imagesNo
custom_tagsNo
enable_statsNo
azure_attributesNo
gcp_attributesNo
aws_attributesNo
instance_pool_typeNoStandard / SPECIALIZED GPU pool type (mutually exclusive with node_type_id)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

Annotations only include readOnlyHint=false, which aligns with the 'Create' action. However, the description lacks any behavioral transparency about what happens after creation (e.g., whether the pool is immediately available, resource usage, side effects, or error cases). Given the minimal annotations, more behavioral context is needed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, making it concise. However, it is too brief and lacks structure; it does not break down the operation or provide any headings or lists. While not verbose, the brevity sacrifices clarity and completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 15 parameters, low schema coverage (27%), and no parameter descriptions in the tool description, the description is severely incomplete. It fails to explain the purpose of the pool, cloud-specific attributes, or how to choose between node_type_id and instance_pool_type. The presence of an output schema does not compensate for the lack of input guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 27%, meaning most parameters lack descriptions. The tool description does not add any parameter explanations beyond what the schema provides. For parameters like aws_attributes or disk_spec with no schema description, the description fails to clarify their purpose. Baseline for low coverage is higher, so a score of 2 is warranted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a new instance pool' uses a specific verb and resource, clearly indicating the creation action. It distinguishes from sibling tools like pools_edit, pools_delete, and pools_get by focusing on creation. However, it could be more explicit about what an instance pool is or differentiate from similar create tools like clusters_create.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 vs alternatives such as pools_edit for updates, or whether prerequisites exist. There is no mention of required parameters beyond the single required one, or any context for when this operation is appropriate.

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

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