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steven0lisa

Dataiku DSS MCP Server

by steven0lisa

get_code_environments

Retrieve all available Python and R code environments in Dataiku DSS, with optional filtering by project key.

Instructions

List available Python/R environments

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_keyNoProject identifier (optional)
Behavior2/5

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

No annotations provided, and description only states basic function. Does not disclose whether it requires authentication, rate limits, or what constitutes 'available' environments.

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 sentence with no wasted words, but slightly under-specified for a tool with no output schema or annotations.

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?

Despite simplicity, lack of output schema means agent won't know what information is returned; description insufficient for full understanding.

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 provides description for the only parameter (optional project_key), and description adds no further meaning. Schema coverage is 100%, so baseline 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?

Description uses specific verb 'List' and resource 'available Python/R environments', clearly distinguishing from sibling tools that operate on datasets, scenarios, 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 guidance on when to use this tool versus alternatives; no mention of prerequisites or context for querying environments.

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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