Is the Panels dashboard compatible with standard FTC telemetry?

Yes, the Telemetry Plugin automatically mirrors the standard Driver Hub output, allowing for easy integration with existing codebases.

What is the default address for the Panels dashboard?

When connected to the robot controller's Wi-Fi, the dashboard is typically accessible at http://192.168.43.1:8001.

Can I tune variables while the robot is running?

Yes, by using the @Configurable annotation on public static fields, you can adjust values live from the dashboard without restarting your OpMode.

Does this skill help with PID tuning?

Yes, it provides patterns for the Graph Plugin to visualize target vs. current positions over time, which is essential for PID controller validation.

How do I add the Panels dependency to my FTC project?

Add implementation 'com.bylazar:fullpanels:1.0.6' to your TeamCode build.gradle file to enable the dashboard features.

Panels FTC Dashboard

Name: Panels FTC Dashboard
Author: ncssm-robotics

byncssm-robotics

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Analytics & Monitoring

Simplifies FTC robot debugging and configuration by integrating telemetry, real-time variable tuning, and live graphing via the Panels dashboard.

The Panels skill for Claude Code provides specialized guidance for FIRST Tech Challenge (FTC) developers to implement the Panels web-based dashboard into their robot control systems. It streamlines the process of setting up text-based telemetry, visualizing performance data through the Graph Plugin, and enabling real-time parameter adjustments using the @Configurable annotation. By offering structured implementation patterns for debugging and monitoring, this skill helps teams optimize PID controllers, track sensor data, and manage OpModes more effectively during testing and competition.

Key Features

012 GitHub stars

02Remote OpMode control and gamepad monitoring

03Live variable tuning via @Configurable annotations

04Real-time telemetry and data visualization

05PID controller optimization through the Graph Plugin

06Offline debugging data capture for remote replay

Use Cases

01Tuning PID coefficients live without redeploying robot code

02Monitoring battery levels and network latency during practice matches

03Visualizing motor power and encoder data to debug autonomous pathing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ncssm-robotics/ftc-claude panels

For use in Claude.ai and ChatGPT

Download Skill