beam-ai-team/beam-get-agent-analytics
skills/beam/beam-tools/beam-get-agent-analytics/SKILL.md
Get analytics for a Beam.ai agent including task counts, completion rates, evaluation scores, and performance trends. Load when user says "agent analytics", "beam analytics", "agent performance", "task stats for agent", "how is agent performing", or needs agent metrics.
data-ai
Updated Jul 8, 2026
$ install --global
skillsauthnpx skillsauth add beam-ai-team/beam-next-skills beam-get-agent-analyticsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- beam-get-agent-analytics
- type:
- skill
- version:
- 1.0
- description:
- Get analytics for a Beam.ai agent including task counts, completion rates,
- author:
- Hassaan Ahmed
- category:
- integrations
- platform:
- Beam AI
- updated:
- 2026-01-02
- visibility:
- team
Beam Get Agent Analytics
Retrieve analytics and performance metrics for a Beam.ai agent.
Safety Contract
This skill is read-only for Beam state. Before saving or sharing analytics output, show the workspace, agent ID, date range, destination path, and whether the output includes task/customer-sensitive fields. Require explicit user approval in the current turn before exporting reports outside the local workspace. Do not create, retry, approve, or update tasks from this skill.
When to Use
- Check agent performance over a time period
- View task completion rates and failure rates
- Analyze evaluation scores and trends
- Compare current period with previous period (deltas)
- Generate performance reports
Prerequisites
.env file at project root:
# Beam.ai - BID instance (default)
BEAM_API_KEY=<bid-api-key>
BEAM_WORKSPACE_ID=<bid-workspace-id>
# Beam.ai - Production instance
BEAM_API_KEY_PROD=<prod-api-key>
BEAM_WORKSPACE_ID_PROD=<prod-workspace-id>
Dependencies: pip install requests python-dotenv
Quick Start
# Get analytics for last 7 days
python 03-skills/beam-get-agent-analytics/scripts/get_agent_analytics.py <agent_id>
# Get analytics for specific date range
python 03-skills/beam-get-agent-analytics/scripts/get_agent_analytics.py <agent_id> \
--start 2024-01-01 --end 2024-01-31
# Get analytics for last 30 days
python 03-skills/beam-get-agent-analytics/scripts/get_agent_analytics.py <agent_id> --days 30
# Use production workspace
python 03-skills/beam-get-agent-analytics/scripts/get_agent_analytics.py <agent_id> --workspace prod
# Output as JSON
python 03-skills/beam-get-agent-analytics/scripts/get_agent_analytics.py <agent_id> --json
Workspaces
| Workspace | API Endpoint | Default |
|-----------|--------------|---------|
| bid | api.bid.beamstudio.ai | Yes |
| prod | api.beamstudio.ai | No |
CLI Reference
| Flag | Description | Default |
|------|-------------|---------|
| agent_id | Agent ID (required) | - |
| --start, -s | Start date (YYYY-MM-DD) | 7 days ago |
| --end, -e | End date (YYYY-MM-DD) | today |
| --days, -d | Look back N days (1,7,14,30,90) | 7 |
| --workspace, -w | Workspace: bid or prod | bid |
| --json | Output as JSON | false |
| --output, -o | Save to file | - |
Response Fields
Current Period Metrics
| Field | Description |
|-------|-------------|
| totalTasks | Total tasks in period |
| completedTasks | Successfully completed tasks |
| failedTasks | Failed tasks |
| averageEvaluationScore | Average eval score (0-100) |
| averageRuntimeSeconds | Avg task runtime |
| totalRuntimeSeconds | Total runtime |
| positiveFeedbackCount | Tasks with positive feedback |
| negativeFeedbackCount | Tasks with negative feedback |
| consentRequiredCount | Tasks requiring user consent |
Period Deltas (vs previous period)
| Field | Description |
|-------|-------------|
| totalTasksDelta | Change in total tasks |
| completedTasksDelta | Change in completed tasks |
| failedTasksDelta | Change in failed tasks |
| averageEvaluationScoreDelta | Change in eval score |
| averageRuntimeSecondsDelta | Change in runtime |
Daily Chart Data
Array of daily stats with:
date: Date (YYYY-MM-DD)completedCount: Completed tasks that dayfailedCount: Failed tasks that dayaverageEvaluationScore: Avg score that day
Example Output
Agent Analytics: My Agent
Period: 2024-01-01 to 2024-01-31
Workspace: prod
=== CURRENT PERIOD ===
Total Tasks: 150
Completed: 135 (90.0%)
Failed: 15 (10.0%)
Avg Eval Score: 87.5
Avg Runtime: 45.7s
Total Runtime: 6,855s (1.9 hrs)
Feedback:
Positive: 120
Negative: 10
Consent Required: 25
=== VS PREVIOUS PERIOD ===
Total Tasks: +15.5%
Completed: +12.3%
Failed: -5.2%
Eval Score: +4.5%
Runtime: -8.7%
=== DAILY TREND (last 7 days) ===
Date | Completed | Failed | Eval Score
-----------+-----------+--------+-----------
2024-01-25 | 42 | 8 | 87.5
2024-01-26 | 38 | 5 | 89.2
2024-01-27 | 45 | 3 | 91.0
...
API Details
Uses Beam.ai analytics endpoint:
- Endpoint:
GET /agent-tasks/analytics - Required params:
agentId,startDate,endDate - Response: HTTP 200 with JSON body
Error Handling
| Error | Solution |
|-------|----------|
| BEAM_API_KEY not found | Add to .env file |
| 401 Unauthorized | Verify API key is valid |
| 404 Not Found | Agent ID doesn't exist |
| 400 Bad Request | Check date format (YYYY-MM-DD) |
Related Skills
beam-debug-issue-tasks- Debug failed tasksbeam-retry-tasks- Retry failed tasksbeam-get-task-details- Get details for a specific task
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