> ## Documentation Index > Fetch the complete documentation index at: https://compass.docs.sunnyscoach.com/llms.txt > Use this file to discover all available pages before exploring further. # Agent Performance Summary > Retrieves high-level metrics for agent performance and email assignment efficiency within the given date range. - Includes statistics on **time to assign agents** and **number of agents per conversation**. - If no `startDate` or `endDate` is provided, defaults to the last 7 days (a week from today). Retrieves high-level metrics for agent performance and email assignment efficiency within the given date range. Includes statistics on time to assign agents and number of agents per conversation. ## Request ### Headers | Name | Type | Required | Description | | ------------- | ------ | -------- | ------------ | | Authorization | string | Yes | Bearer token | ### Path Parameters | Parameter | Type | Required | Description | | --------- | ------ | -------- | ------------------------------------------------------------------- | | startDate | string | Yes | Start date of the range (ISO 8601). Defaults to 7 days before today | | endDate | string | Yes | End date of the range (ISO 8601). Defaults to today | #### Parameter Format * **Format**: `YYYY-MM-DD` (ISO 8601 date) * **Timezone**: UTC * **Default**: Last 7 days if not provided ## Response ### 200 OK - Successfully retrieved agent high-level statistics ```json theme={null} { "message": "", "data": { "agentAssignmentTimes": { "first": { "min": 1, "max": 45, "average": 8.5, "median": 6.2 }, "overall": { "min": 2, "max": 120, "average": 15.8, "median": 12.5 } }, "agentsCount": { "min": 1, "max": 5, "average": 1.8, "median": 1 } } } ``` ### 401 Unauthorized ```json theme={null} { "error": { "code": "UNAUTHORIZED", "message": "Missing or invalid token" } } ``` ### 500 Internal Server Error ```json theme={null} { "error": { "code": "SERVER_ERROR", "message": "Internal server error" } } ``` ## Example ```bash theme={null} curl -X GET 'http://localhost:2000/email-meter/stats/agents-highlevel/2025-10-01/2025-10-07' \ -H 'Authorization: oBearerBearer your-jwt-token' ' ``` ## Data Fields Explained ### Agent Assignment Times | Field | Type | Description | | ------- | ------ | ------------------------------------------ | | first | object | Time to assign first agent (minutes) | | overall | object | Time to complete all assignments (minutes) | #### Assignment Time Metrics | Field | Type | Description | | ------- | ------ | --------------------------------- | | min | number | Minimum assignment time (minutes) | | max | number | Maximum assignment time (minutes) | | average | number | Average assignment time (minutes) | | median | number | Median assignment time (minutes) | ### Agents Count | Field | Type | Description | | ------- | ------ | ------------------------------- | | min | number | Minimum agents per conversation | | max | number | Maximum agents per conversation | | average | number | Average agents per conversation | | median | number | Median agents per conversation | ## Performance Metrics ### Assignment Efficiency * **Excellent**: \< 5 minutes to first assignment * **Good**: 5-10 minutes to first assignment * **Needs Improvement**: 10-20 minutes * **Poor**: > 20 minutes ### Agent Utilization * **Optimal**: 1-2 agents per conversation * **Collaborative**: 2-3 agents per conversation * **Overstaffed**: > 3 agents per conversation * **Understaffed**: Consistent 1 agent with long assignments ## Use Cases * **Team Performance**: Monitor agent assignment efficiency * **Resource Planning**: Optimize agent allocation * **Process Improvement**: Identify bottlenecks in assignment * **Quality Assurance**: Ensure timely agent responses * **Capacity Analysis**: Understand agent workload distribution ## Analysis Examples ### Assignment Performance ```javascript theme={null} const assignmentPerformance = { excellent: data.data.agentAssignmentTimes.first.average < 5, good: data.data.agentAssignmentTimes.first.average >= 5 && data.data.agentAssignmentTimes.first.average < 10, needsImprovement: data.data.agentAssignmentTimes.first.average >= 10 }; ``` ### Workload Distribution ```javascript theme={null} const workloadDistribution = { optimal: data.data.agentsCount.average <= 2, collaborative: data.data.agentsCount.average > 2 && data.data.agentsCount.average <= 3, overstaffed: data.data.agentsCount.average > 3 }; ``` ## Best Practices 1. **Monitoring**: Track assignment times regularly 2. **Alerts**: Set up alerts for slow assignments 3. **Balancing**: Distribute workload evenly across agents 4. **Training**: Use data for agent performance training 5. **Optimization**: Continuously improve assignment processes ## Performance Targets ### Assignment Time Targets * **First Assignment**: \< 10 minutes (80% of conversations) * **Complete Assignment**: \< 20 minutes (90% of conversations) * **Maximum Time**: \< 60 minutes (99% of conversations) ### Agent Count Targets * **Average**: 1.5-2.5 agents per conversation * **Maximum**: \< 5 agents per conversation * **Consistency**: Low variance in agent counts ## Related Endpoints * Use `/email-meter/stats/agents-detailed` for per-agent statistics * Use `/email-meter/stats/response-times` for overall response metrics * Use `/email-meter/stats/resolved-times` for resolution analysis ## Notes * Assignment times are calculated from email receipt to agent assignment * Times exclude automated assignments and routing * Only human agent assignments are included * Business hours are considered by default * Weekends and holidays may affect average times ## OpenAPI ````yaml GET /email-meter/stats/agents-highlevel/{startDate}/{endDate} openapi: 3.0.3 info: title: COMPASS API version: 1.0.0 description: OpenAPI specification for the Compass backend routes. servers: - url: http://localhost:2000 description: Local development server security: [] tags: - name: Auth description: >- Authentication and session management endpoints (OAuth and session validation) - name: Users description: Operations for managing user records - name: Departments description: Operations for managing departments - name: Email Meter description: APIs to get Email Meter Stats - name: HubSpot Tickets description: Feedback APIs - name: Permissions description: Permissions APIs - name: Transcription description: Transcription APIs paths: /email-meter/stats/agents-highlevel/{startDate}/{endDate}: get: tags: - Email Meter summary: Get high-level agent performance statistics description: > Retrieves high-level metrics for agent performance and email assignment efficiency within the given date range. - Includes statistics on **time to assign agents** and **number of agents per conversation**. - If no `startDate` or `endDate` is provided, defaults to the last 7 days (a week from today). parameters: - name: startDate in: path required: true schema: type: string format: date description: > Start date of the range (ISO 8601). Defaults to 7 days before today if not provided. example: '2025-10-01' - name: endDate in: path required: true schema: type: string format: date description: > End date of the range (ISO 8601). Defaults to today if not provided. example: '2025-10-07' responses: '200': description: Successfully retrieved agent high-level statistics content: application/json: schema: type: object properties: message: type: string data: type: object properties: agentAssignmentTimes: type: object description: >- Metrics about how quickly agents were assigned to conversations properties: first: $ref: '#/components/schemas/StatsSummary' overall: $ref: '#/components/schemas/StatsSummary' agentsCount: $ref: '#/components/schemas/StatsSummary' '401': description: Unauthorized (missing or invalid token) '500': description: Server error security: - bearerAuth: [] components: schemas: StatsSummary: type: object description: Basic statistical summary (min, max, average, median, count) properties: min: type: number format: float description: Minimum observed value (in hours for time-based metrics) example: 0.5 max: type: number format: float description: Maximum observed value (in hours for time-based metrics) example: 26.5 average: type: number format: float description: Arithmetic average example: 4.2 median: type: number format: float description: Statistical median (if used differently in your code) example: 3.9 count: type: integer description: Number of samples used to compute these stats example: 200 securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: JWT ````