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SAS MCP Server

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List Compute Columns

list_compute_columns
Read-onlyIdempotent

List columns of a SAS table in a compute context to inspect its structure. Retrieve column names and metadata for tables in SAS libraries.

Instructions

List the columns of a table in a SAS library within a compute context.

Runs in the reusable per-user compute session for the context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of columns to return (default 50).
startNoOffset of the first column to return (default 0).
table_nameYesName of the table within the library.
filter_nameNoOptional name filter (substring match).
library_nameYesName of the SAS library/libref (e.g. 'WORK', 'SASHELP').
compute_context_nameYesName of the compute context (see list_compute_contexts).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A4.1/5.0
Behavior4/5

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

The description adds a meaningful behavioral detail beyond the annotations: 'Runs in the reusable per-user compute session for the context.' This tells the agent the operation depends on an existing compute session. The readOnlyHint and destructiveHint already cover safety, and no contradiction exists.

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?

Two short sentences earn their place: the first states the action and scope, the second adds execution context. There is no redundancy or filler.

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?

With a fully described input schema, an output schema, and annotations covering safety, the description is sufficient for this simple listing operation. It adds the key execution context about the compute session, and nothing essential is missing.

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 the baseline is 3. The description clarifies the relationship among compute_context_name, library_name, and table_name, but it does not add parameter-level detail beyond what the schema already provides.

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 uses a specific verb and resource: 'List the columns of a table in a SAS library within a compute context.' This clearly differentiates it from sibling tools like list_compute_tables (tables) and list_compute_libraries (libraries), and the scope is unambiguous.

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?

The description provides context by noting it runs in a reusable per-user compute session, but it does not explicitly say when to use this tool versus alternatives such as get_castable_columns or list_compute_tables. Usage must be inferred from the resource type being listed.

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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