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steven0lisa

Dataiku DSS MCP Server

by steven0lisa

validate_recipe_syntax

Check Python or SQL syntax of a recipe in a Dataiku DSS project, optionally using provided code instead of the stored recipe code.

Instructions

Validate Python/SQL syntax of a recipe

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_keyYesThe project key
recipe_nameYesName of the recipe
codeNoOptional code to validate (uses recipe code if not provided)
Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits like side effects, error reporting, or whether it modifies state. For a validation tool, this is a gap.

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 a single, front-loaded sentence with no wasted words. It is concise and clear.

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?

For a simple validation tool without an output schema, the description could explain what the tool returns (e.g., success/failure or error list). It 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 description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema as the 'code' parameter already explains its optionality.

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 'Validate Python/SQL syntax of a recipe' is specific with a verb and resource, clearly distinguishing it from sibling tools like run_recipe or test_recipe_dry_run.

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, such as when code needs validation before running a recipe. The context is implied but not explicit.

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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