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langfuse-mcp-java

get_model

get_model
Destructive

Retrieve detailed pricing, configuration, and metadata for a specific AI model by its ID to manage costs and track usage in LLM applications.

Instructions

Returns a single model definition by its ID. Returns: id, modelName, matchPattern, unit, inputPrice, outputPrice, totalPrice, startDate, tokenizerId, isLangfuseManaged, projectId. modelId is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelIdYesThe model ID. Required.
Behavior2/5

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

The description claims a simple read operation ('Returns'), but annotations indicate destructiveHint=true and readOnlyHint=false, suggesting side effects or mutation. The description completely fails to explain what gets destroyed, modified, or what the openWorldHint implies regarding external resource access.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is efficient. However, listing all 11 return fields in prose is bulky (necessary given no output schema exists, but poorly structured). The final sentence 'modelId is required' is redundant with the schema.

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 compensates for the missing output schema by enumerating return fields. However, given the destructive annotation and complex sibling ecosystem, it lacks explanation of behavioral implications and side effects that the agent should know before invoking.

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?

With 100% schema coverage, the schema adequately documents the modelId parameter. The description adds no semantic value beyond repeating 'modelId is required' which is already evident in the schema's required array.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Returns a single model definition by its ID', specifying the verb (Returns), resource (model definition), and scope (single by ID). This effectively distinguishes it from sibling tools like list_models (which returns multiple) and create_model/delete_model.

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 provided on when to use this tool versus alternatives like list_models (for browsing) or fetch_traces (which uses different terminology). No mention of prerequisites or typical use cases.

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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