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List compute resources

list_compute
Read-only

List Databricks clusters and SQL warehouses with states, node types, and Spark runtime versions. Filter by name to inspect compute resources for planning or troubleshooting.

Instructions

List compute: all-purpose clusters and SQL warehouses with current state, available node types (cores, memory, GPUs, Photon support) and Databricks Runtime (Spark) versions.

Safety classification: READ_ONLY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoCase-insensitive substring filter on name/id (node_types, spark_versions).
resourceNosummary: clusters + warehouses with states; or one resource type.summary
page_sizeNoMax items to return (server caps this).
page_tokenNonext_page_token from a previous response.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
pageNo
planNo
toolYes
actionNo
safetyNo
statusNosuccess
summaryYes
warningsNo
next_stepsNoSuggested follow-up calls.
request_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the 'Safety classification: READ_ONLY' sentence merely restates structured data and earns no credit. The description adds useful context about what the listing exposes (current state, node types, runtime versions), but says nothing about auth needs, result caps, or pagination behavior beyond what the schema already carries.

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

Conciseness4/5

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

Front-loaded and compact: the core scope sentence comes first and reads cleanly. The trailing 'Safety classification: READ_ONLY' line is pure redundancy against the readOnlyHint annotation and should be dropped, which is the only real waste.

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

Completeness4/5

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

With an output schema present, the description need not explain return values, and it does adequately convey the two resource families and their attributes. Given 4 parameters at full schema coverage and rich annotations, the remaining gap is the absence of any guidance on narrowing results with the filter or handling pagination.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters (filter, resource, page_size, page_token) are already documented with semantics and defaults. The description only loosely echoes the resource categories through its mention of node types and runtime versions, adding little beyond the enum's own description. Baseline 3 is appropriate.

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

Purpose5/5

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

States a specific verb ('List') plus the concrete resource set it covers ('all-purpose clusters and SQL warehouses') and enumerates the returned attributes (state, node types, Photon support, Databricks Runtime versions). This cleanly separates it from the manage_cluster and manage_sql_warehouse siblings, which are mutation-oriented.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the verb and the scope statement, but there is no explicit guidance on when to call this versus manage_cluster, manage_sql_warehouse, or get_table_stats_and_schema, and no mention of prerequisites or follow-up tools. An agent can infer the read-only inventory role but gets no routing help.

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