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alan4041207

mcp-altair-studio

by alan4041207

altair_generate_attribute

Creates a new calculated column by applying a RapidMiner expression to existing attributes.

Instructions

Create a new derived/calculated column using a RapidMiner expression, e.g. attributeName="profit", expression="revenue - cost". Covers action 21 (create new variables via formulas).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvFileNoAbsolute path to a local CSV file to read directly (bypasses the repository). Use this OR repositoryEntry.
expressionYesRapidMiner expression syntax, e.g. "revenue - cost" or "log(price)".
attributeNameYes
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?

No annotations are provided, so the description carries full burden. It states the tool creates a new column but does not disclose behavioral traits such as whether it modifies the dataset in place, if it is reversible, or what happens if an attribute with the same name exists. This is insufficient for a mutation tool.

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 extremely concise with two sentences, including an example and a reference to action 21. Every sentence adds value; there is no redundancy.

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

Completeness2/5

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

Given 4 parameters, no output schema, and missing annotations, the description is incomplete. It lacks details on parameter relationships (csvFile vs repositoryEntry), return value, and usage context (e.g., whether it can be undone). Key gaps reduce the agent's ability to use the tool 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 75%, slightly below the 80% threshold, so the description should supplement. The description provides an example for attributeName and expression, adding context where the schema lacks description for attributeName. However, it does not explain the mutual exclusivity of csvFile and repositoryEntry, which the schema already hints at.

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 creates a new derived/calculated column using a RapidMiner expression, with an explicit example. It distinguishes from sibling tools like altair_clean_data or altair_normalize_data by specifying 'generate attribute' and referencing action 21, which is unique among siblings.

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 implies usage when a derived column is needed, but provides no explicit guidance on when to use this tool versus alternatives (e.g., altair_clean_data) or when not to use it. No exclusions or prerequisites are mentioned.

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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