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sassoftware

SAS MCP Server

Official
by sassoftware

run_ml_project

Run an AutoML pipeline automation project by providing its project ID to start model training and evaluation.

Instructions

Run an AutoML pipeline automation project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesID of the project to run.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations exist, and description lacks any behavioral traits (e.g., whether it starts an async job, required permissions, or side effects). The description is too brief.

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?

Single clear sentence with no waste. Concise but acceptable for a simple trigger action.

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

Completeness3/5

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

Given output schema exists (unseen), description could still explain whether execution is synchronous/asynchronous or return value. Lacks context on expected behavior.

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 covers 100% of parameters with clear description ('ID of the project to run'). Description adds no extra meaning beyond 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?

Description clearly states 'Run an AutoML pipeline automation project.' Verb and resource are specific, distinguishing it from siblings like 'create_ml_project' and 'cancel_job'.

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?

No guidance on when to use this tool vs alternatives (e.g., when to start a job vs submit_batch_job). No prerequisites or conditions provided.

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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