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Rubrik MCP

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by rubrikinc

rsc_describe_operation_full

Read-only

Retrieves a Rubrik GraphQL operation signature with input and enum types expanded inline, plus return fields, so you can construct correct queries without guessing.

Instructions

Get an operation's signature with all input types expanded inline.

Returns an operation's argument signature with all input/enum types expanded inline — recursively up to depth levels. Combines the operation lookup and rsc_describe_type into one call so you have everything needed to construct a correct query without guessing.

Args: name: camelCase operation name (e.g. "azureNativeVirtualMachines"). operation_type: "query" or "mutation". depth: How many levels of input types to expand (default 2).

Returns: Dict with operation details plus: - "expanded_types": all referenced input/enum type definitions - "return_type_fields": object/interface types in the return type, expanded 2 levels deep (connection wrapper → node fields), so you know exactly which fields are selectable in the query body. Interface types include an "inline_fragments" key listing each concrete implementor and its fields — these fields are ONLY accessible via "... on TypeName { field }" inline fragments in your query; they cannot be queried directly on the interface.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
depthNo
operation_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), so the bar is lower. The description adds genuine behavioral context beyond that: recursive expansion 'up to depth levels' and the important constraint that interface fields are ONLY accessible via inline fragments. It discloses output structure, which matters since no output schema exists.

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?

The opening sentence is front-loaded and the Args/Returns structure is easy to scan. The return section is somewhat verbose, but since there is no output schema, that detail earns its place.

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 0% schema coverage and no output schema, the description must carry both input and output detail, and it does: it documents all three parameters and describes the return payload keys (expanded_types, return_type_fields, inline_fragments). Nothing critical for correct invocation is missing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description carries full parameter burden and does so well: it defines name format (camelCase, with example), operation_type enum values ('query' or 'mutation'), and depth semantics including its default of 2. This fully compensates for the empty schema.

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?

States a specific verb and resource: 'Get an operation's signature with all input types expanded inline.' It further distinguishes itself from the sibling rsc_describe_type by noting it 'combines the operation lookup and rsc_describe_type into one call.' Clear and differentiated, though the exact GraphQL-specific scope could be tightened.

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?

It implies when to use it ('so you have everything needed to construct a correct query without guessing') and references the sibling it supersedes, rsc_describe_type. However, there is no explicit when-not guidance or clear routing rule versus calling rsc_describe_type directly — usage is inferred rather than stated.

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