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Describe Report Objects

describe_report_objects
Read-onlyIdempotent

Need to know what a SAS Visual Analytics report can contain? Look up report operations and object contracts from a bundled catalog to learn data roles, examples, and build reports without guesswork.

Instructions

Discover what a Visual Analytics report can contain — operations and objects.

Call this to learn how to build a report before calling apply_report_operations. It reads a bundled catalog (no network), so it is the cheap way to look up an object's data roles instead of guessing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoRestrict the catalog to one category.
operationNoAn operation key (e.g. ``"addData"``, ``"applyDataView"``) for its full shape, example, and notes.
object_typeNoA schema key (e.g. ``"barChart"``, ``"scatterPlot"``) or colloquial alias for its contract and example.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.7.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful behavioral context: it reads a bundled catalog with no network access, making it a cheap and reliable lookup. This goes beyond the structured annotations.

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

Conciseness5/5

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

The description is compact and front-loaded: the core purpose appears in the first sentence, and the usage guidance follows in the second. Every sentence earns its place with no filler or redundancy.

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

Completeness5/5

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

The description covers what the tool does, when to use it, how it behaves, and why it is preferable in this situation. Combined with full schema descriptions and an output schema, nothing essential is missing for an agent to select and invoke it correctly.

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%, and each parameter already has a meaningful description with examples. The tool description does not need to restate parameter-level details, so the baseline score of 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?

The description clearly states what the tool does: discover what a Visual Analytics report can contain—operations and objects. It uses a specific verb and resource, and distinguishes itself from apply_report_operations, making its purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly says to call this before apply_report_operations to learn how to build a report, and frames it as the cheap way to look up data roles instead of guessing. This gives the agent a clear selection rule relative to a key sibling tool.

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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