> ## Documentation Index > Fetch the complete documentation index at: https://docs.scorecard.io/llms.txt > Use this file to discover all available pages before exploring further. # List Metrics > List Metrics configured for the specified Project. Metrics are returned in reverse chronological order. ## OpenAPI ````yaml get /projects/{projectId}/metrics openapi: 3.1.0 info: title: Scorecard API description: REST API for Scorecard version: 1.0.0 servers: - url: https://api2.scorecard.io/api/v2 security: - ApiKeyAuth: [] paths: /projects/{projectId}/metrics: get: summary: List Metrics description: >- List Metrics configured for the specified Project. Metrics are returned in reverse chronological order. operationId: listMetrics parameters: - in: path name: projectId description: The ID of the Project to list Metrics for. schema: type: string example: '314' required: true - in: query name: limit description: >- Maximum number of items to return (1-100). Use with `cursor` for pagination through large sets. schema: type: integer exclusiveMinimum: 0 default: 20 example: 20 - in: query name: cursor description: >- Cursor for pagination. Pass the `nextCursor` from the previous response to get the next page of results. schema: type: string example: '123' responses: '200': description: Successfully retrieved Metrics. content: application/json: schema: type: object properties: data: type: array items: $ref: '#/components/schemas/Metric' nextCursor: type: - string - 'null' hasMore: type: boolean total: type: integer minimum: 0 required: - data - nextCursor - hasMore examples: List Metrics: summary: List Metrics description: >- Example response showing metrics with different evaluation and output types. value: data: - id: '456' name: Response Accuracy description: Evaluates if the response is factually accurate outputType: boolean evalType: ai guidelines: >- Check if the response contains factually correct information promptTemplate: >- Please evaluate if the following response is factually accurate: {{response}} evalModelName: gpt-4o temperature: 0.1 - id: '457' name: Response Quality description: Human review of quality outputType: float evalType: human guidelines: Rate the coherence of the response (0-1). passingThreshold: 0.8 nextCursor: null hasMore: false '401': $ref: '#/components/responses/UnauthenticatedError' '500': $ref: '#/components/responses/ServiceError' x-codeSamples: - lang: JavaScript source: |- import Scorecard from 'scorecard-ai'; const client = new Scorecard({ apiKey: 'My API Key', }); // Automatically fetches more pages as needed. for await (const metric of client.metrics.list('314')) { console.log(metric); } - lang: Python source: |- from scorecard_ai import Scorecard client = Scorecard( api_key="My API Key", ) page = client.metrics.list( project_id="314", ) page = page.data[0] print(page) - lang: cURL source: |- curl https://api2.scorecard.io/api/v2/projects/$PROJECT_ID/metrics \ -H "Authorization: Bearer $SCORECARD_API_KEY" components: schemas: Metric: anyOf: - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: ai description: AI-based evaluation type. guidelines: type: string description: Guidelines for AI evaluation on how to score the metric. promptTemplate: type: string description: >- The complete prompt template for AI evaluation. Should include placeholders for dynamic content. evalModelName: type: string default: gpt-4o description: The AI model to use for evaluation. temperature: type: number minimum: 0 maximum: 2 default: 0 description: The temperature for AI evaluation (0-2). outputType: type: string const: int description: Integer output type. passingThreshold: type: integer minimum: 1 maximum: 5 default: 4 description: >- The threshold for determining pass/fail from integer scores (1-5). required: - id - name - description - evalType - guidelines - promptTemplate - evalModelName - temperature - outputType - passingThreshold description: A Metric with AI evaluation and integer output. title: AI int metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: human description: Human-based evaluation type. guidelines: type: string description: Guidelines for human evaluators. outputType: type: string const: int description: Integer output type. passingThreshold: type: integer minimum: 1 maximum: 5 default: 4 description: >- The threshold for determining pass/fail from integer scores (1-5). required: - id - name - description - evalType - guidelines - outputType - passingThreshold description: A Metric with human evaluation and integer output. title: Human int metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: heuristic description: Heuristic-based evaluation type. guidelines: type: string description: Guidelines for heuristic evaluation logic. outputType: type: string const: int description: Integer output type. passingThreshold: type: integer minimum: 1 maximum: 5 default: 4 description: >- The threshold for determining pass/fail from integer scores (1-5). required: - id - name - description - evalType - guidelines - outputType - passingThreshold description: A Metric with heuristic evaluation and integer output. title: Heuristic int metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: ai description: AI-based evaluation type. guidelines: type: string description: Guidelines for AI evaluation on how to score the metric. promptTemplate: type: string description: >- The complete prompt template for AI evaluation. Should include placeholders for dynamic content. evalModelName: type: string default: gpt-4o description: The AI model to use for evaluation. temperature: type: number minimum: 0 maximum: 2 default: 0 description: The temperature for AI evaluation (0-2). outputType: type: string const: float description: Float output type (0-1). passingThreshold: type: number minimum: 0 maximum: 1 default: 0.9 description: Threshold for determining pass/fail from float scores (0.0-1.0). required: - id - name - description - evalType - guidelines - promptTemplate - evalModelName - temperature - outputType - passingThreshold description: A Metric with AI evaluation and float output. title: AI float metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: human description: Human-based evaluation type. guidelines: type: string description: Guidelines for human evaluators. outputType: type: string const: float description: Float output type (0-1). passingThreshold: type: number minimum: 0 maximum: 1 default: 0.9 description: Threshold for determining pass/fail from float scores (0.0-1.0). required: - id - name - description - evalType - guidelines - outputType - passingThreshold description: A Metric with human evaluation and float output. title: Human float metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: heuristic description: Heuristic-based evaluation type. guidelines: type: string description: Guidelines for heuristic evaluation logic. outputType: type: string const: float description: Float output type (0-1). passingThreshold: type: number minimum: 0 maximum: 1 default: 0.9 description: Threshold for determining pass/fail from float scores (0.0-1.0). required: - id - name - description - evalType - guidelines - outputType - passingThreshold description: A Metric with heuristic evaluation and float output. title: Heuristic float metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: ai description: AI-based evaluation type. guidelines: type: string description: Guidelines for AI evaluation on how to score the metric. promptTemplate: type: string description: >- The complete prompt template for AI evaluation. Should include placeholders for dynamic content. evalModelName: type: string default: gpt-4o description: The AI model to use for evaluation. temperature: type: number minimum: 0 maximum: 2 default: 0 description: The temperature for AI evaluation (0-2). outputType: type: string const: boolean description: Boolean output type. required: - id - name - description - evalType - guidelines - promptTemplate - evalModelName - temperature - outputType description: A Metric with AI evaluation and boolean output. title: AI boolean metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: human description: Human-based evaluation type. guidelines: type: string description: Guidelines for human evaluators. outputType: type: string const: boolean description: Boolean output type. required: - id - name - description - evalType - guidelines - outputType description: A Metric with human evaluation and boolean output. title: Human boolean metric - type: object properties: id: type: string description: The ID of the Metric. name: type: string description: The name of the Metric. description: type: - string - 'null' default: null description: The description of the Metric. evalType: type: string const: heuristic description: Heuristic-based evaluation type. guidelines: type: string description: Guidelines for heuristic evaluation logic. outputType: type: string const: boolean description: Boolean output type. required: - id - name - description - evalType - guidelines - outputType description: A Metric with heuristic evaluation and boolean output. title: Heuristic boolean metric description: >- A Metric defines how to evaluate system outputs against expected results. ApiError: type: object properties: code: type: string message: type: string details: type: object additionalProperties: true x-stainless-any: true required: - code - message - details description: An API error. responses: UnauthenticatedError: description: Error indicating that the request is not authenticated. content: application/json: schema: $ref: '#/components/schemas/ApiError' examples: Authentication failure: value: code: UNAUTHORIZED message: Invalid or missing authentication token details: {} summary: Authentication failure description: >- Error returned when authentication credentials are invalid or missing. ServiceError: description: >- An internal service error indicating an issue with the Scorecard service. content: application/json: schema: $ref: '#/components/schemas/ApiError' examples: Internal error: value: code: INTERNAL_ERROR message: An unexpected error occurred while processing your request. details: {} summary: Internal error description: Generic error when an unexpected internal issue occurs. securitySchemes: ApiKeyAuth: type: http scheme: bearer bearerFormat: starts with ak_ ````