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therealsachin

Langfuse MCP Server

get_observation_detail

Retrieve detailed information about a specific observation by its ID to analyze performance metrics and usage data within Langfuse projects.

Instructions

Get detailed information about a specific observation by ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
observationIdYesThe observation ID to retrieve detailed information for

Implementation Reference

  • Core handler function that fetches the observation detail using the Langfuse client and returns formatted content or error.
    export async function getObservationDetail(
      client: LangfuseAnalyticsClient,
      args: GetObservationDetailArgs
    ) {
      try {
        const observationData = await client.getObservation(args.observationId);
    
        return {
          content: [
            {
              type: 'text' as const,
              text: JSON.stringify(observationData, null, 2),
            },
          ],
        };
      } catch (error) {
        const errorMessage = error instanceof Error ? error.message : String(error);
        return {
          content: [
            {
              type: 'text' as const,
              text: `Error getting observation detail: ${errorMessage}`,
            },
          ],
          isError: true,
        };
      }
    }
  • Zod schema for input validation of the get_observation_detail tool.
    export const getObservationDetailSchema = z.object({
      observationId: z.string().describe('The observation ID to retrieve detailed information for'),
    });
  • src/index.ts:526-539 (registration)
    Tool definition in the allTools array used by listTools handler to expose the tool with its schema.
    {
      name: 'get_observation_detail',
      description: 'Get detailed information about a specific observation by ID.',
      inputSchema: {
        type: 'object',
        properties: {
          observationId: {
            type: 'string',
            description: 'The observation ID to retrieve detailed information for',
          },
        },
        required: ['observationId'],
      },
    },
  • src/index.ts:1062-1065 (registration)
    Dispatch case in the central CallToolRequestSchema handler that parses arguments and invokes the tool handler.
    case 'get_observation_detail': {
      const args = getObservationDetailSchema.parse(request.params.arguments);
      return await getObservationDetail(this.client, args);
    }
  • TypeScript type inferred from the Zod schema for type safety.
    export type GetObservationDetailArgs = z.infer<typeof getObservationDetailSchema>;
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves detailed information, implying a read-only operation, but does not mention any behavioral traits such as authentication requirements, rate limits, error handling, or what 'detailed information' entails. This leaves significant gaps in understanding how the tool behaves.

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, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.

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 the lack of annotations and output schema, the description is incomplete. It does not explain what 'detailed information' includes, how the data is returned, or any prerequisites for use. For a tool that likely returns complex data, this leaves the agent without sufficient context to use it effectively.

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?

The input schema has 100% description coverage, with the parameter 'observationId' clearly documented. The description adds no additional semantic information beyond what the schema provides, such as format examples or constraints. According to the rules, with high schema coverage, the baseline is 3, which is appropriate here.

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 verb ('Get') and resource ('detailed information about a specific observation by ID'), making the purpose unambiguous. However, it does not differentiate this tool from potential siblings like 'get_observations' or 'get_trace_detail', which might retrieve similar types of data, so it falls short of a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. For example, it does not specify if this is for a single observation versus a list from 'get_observations', or if it should be used over other detail tools like 'get_model_detail'. This lack of context leaves the agent without clear usage instructions.

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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