How do I view results for a specific project?

You can use the command `/ar:status [domain]/[name]` to see detailed metrics and the active loop status for a single experiment.

Can I export my experiment data for external reporting?

Yes, you can export the dashboard data to CSV or Markdown formats by using the `--format` and `--output` flags.

What does the 'Change' column represent in the dashboard?

The Change column shows the percentage of improvement or regression compared to the baseline or initial run of that specific experiment.

Does this skill track background tasks?

Yes, it checks for active loop configurations to report whether an experiment is currently running on a schedule, such as hourly or daily intervals.

Experiment Research Dashboard

Name: Experiment Research Dashboard
Author: alirezarezvani

byalirezarezvani

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9,958

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分析与监控

Monitors automated experiment progress, performance metrics, and active research loops across multiple domains.

The Status skill provides a comprehensive control center for the engineering-autoresearch-agent, allowing users to track the lifecycle and results of automated experiments directly within Claude. It surfaces critical data such as run counts, improvement percentages, and best-recorded metrics, while also monitoring active background loops to ensure continuous optimization processes are running as intended. This is particularly useful for developers and researchers managing complex, long-running optimization tasks who need a centralized view of their progress and performance deltas.

主要功能

01Performance delta reporting showing percentage changes from baseline results

02Multi-format data export capabilities supporting both Markdown and CSV for reporting

039,958 GitHub stars

04Granular filtering to view specific experiments or entire functional domains

05Cross-domain experiment tracking and visualization via a centralized dashboard

06Real-time status monitoring of active automation loops and cron schedules

使用场景

01Managing recurring marketing optimization loops across different content segments

02Monitoring API latency improvements and performance gains during automated load testing

03Tracking prompt engineering iterations and scoring for LLM fine-tuning tasks

主要功能

01Performance delta reporting showing percentage changes from baseline results

02Multi-format data export capabilities supporting both Markdown and CSV for reporting

039,958 GitHub stars

04Granular filtering to view specific experiments or entire functional domains

05Cross-domain experiment tracking and visualization via a centralized dashboard

06Real-time status monitoring of active automation loops and cron schedules

使用场景

01Managing recurring marketing optimization loops across different content segments

02Monitoring API latency improvements and performance gains during automated load testing

03Tracking prompt engineering iterations and scoring for LLM fine-tuning tasks