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langfuse-mcp-java

create_score_config

create_score_config
Destructive

Define score configurations to validate and structure future evaluations in Langfuse, supporting numeric, categorical, and boolean data types with optional constraints.

Instructions

Creates a score config definition used to validate or structure future scores. name and dataType are required. For categorical configs, categoriesJson should be a JSON array of {label,value} objects. For numeric configs, minValue and maxValue are optional bounds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesScore config name. Required.
dataTypeYesData type: NUMERIC | CATEGORICAL | BOOLEAN. Required.
categoriesJsonYesOptional categorical options as a JSON array of {label,value} objects.
minValueYesOptional minimum numeric value.
maxValueYesOptional maximum numeric value.
descriptionYesOptional description shown in Langfuse.
Behavior3/5

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

Annotations declare destructiveHint=true and idempotentHint=false, indicating this is a state-mutating creation operation. The description adds domain context about validation/structuring but does not elaborate on side effects, conflict behavior (what happens if name exists), or persistence details beyond what the annotations convey.

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 contains exactly four tight sentences: one for purpose, one for required fields, and two for conditional parameter usage. Every sentence earns its place with no redundant fluff, and the information is front-loaded with the primary 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?

The description covers categorical and numeric configuration patterns but completely omits the BOOLEAN dataType case mentioned in the schema. Additionally, it does not mention the 'description' parameter (documented only in the schema) or discuss return values, though no output schema exists to require this.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3. The description adds crucial semantic value by specifying the conditional logic between data types and their associated parameters (categorical vs. numeric configurations), which is essential for correct invocation but not captured in the flat schema structure.

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 the tool 'Creates a score config definition' with the specific purpose of validating or structuring future scores. The verb and resource are unambiguous, and it distinguishes from sibling tools like get_score_config or update_score_config by focusing on the creation aspect.

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 provides conditional usage guidance for parameters (e.g., 'For categorical configs, categoriesJson should be...' and 'For numeric configs, minValue and maxValue are optional'), which helps users understand when to use specific parameters. However, it lacks explicit guidance on when to use this tool versus alternatives like update_score_config.

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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