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alan4041207

mcp-altair-studio

by alan4041207

altair_descriptive_stats

Compute descriptive statistics (average, min, max, standard deviation, median, count) for every numeric column in a dataset from an Altair AI Studio repository or CSV file.

Instructions

Compute descriptive statistics (average, min, max, standard deviation, median, count) for every numeric column. Covers actions 26-28 (descriptive statistics, distribution summary).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvFileNoAbsolute path to a local CSV file to read directly (bypasses the repository). Use this OR repositoryEntry.
repositoryEntryNoAltair AI Studio repository path, e.g. "//Local Repository/data/customers" or "//Samples/data/Iris". Use this OR csvFile.
Behavior2/5

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

With no annotations, the description carries full burden but only states it computes stats for every numeric column. It does not disclose behavioral traits like handling of non-numeric columns, side effects, or permissions.

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 description is very short (two sentences) and concise. It conveys the purpose without waste, but could include more useful information without being verbose.

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 no output schema, the description does not explain the return format or value. It mentions statistics but lacks details on how results are presented. For a simple computation tool, this is adequate but incomplete.

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 coverage is 100% with both parameters described. The description adds no additional meaning beyond what the schema provides, so 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?

The description clearly states it computes descriptive statistics (average, min, max, standard deviation, median, count) for every numeric column, which is a specific verb+resource. It distinguishes from sibling tools that handle association rules, clustering, cleaning, etc.

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 explicit when-to-use or when-not-to-use guidance is given. It does not mention alternatives among sibling tools or provide context for selecting this tool over others.

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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