// Interact with Lynx DevTool to inspect and debug Lynx applications. Use this skill to list connected clients and sessions, send Chrome DevTools Protocol (CDP) commands, send App commands, and open URLs in Lynx. This is useful for debugging UI issues, inspecting runtime state, or automating interactions with Lynx apps.
| name | lynx-devtool |
| description | Interact with Lynx DevTool to inspect and debug Lynx applications. Use this skill to list connected clients and sessions, send Chrome DevTools Protocol (CDP) commands, send App commands, and open URLs in Lynx. This is useful for debugging UI issues, inspecting runtime state, or automating interactions with Lynx apps. |
This skill allows you to interact with Lynx applications running on connected devices (Android, iOS, Desktop) using the Lynx DevTool CLI.
The CLI is located at <path_to_the_skill>/scripts/index.mjs relative to this skill's directory. You can run it using node.
In the skill directory, use:
node <path_to_the_skill>/scripts/index.mjs <command>
Note: All command outputs are multi-line JSON. You can use jq or Node.js to process the data.
-h, --help: Display help for command.Note: Each subcommand supports the --help flag (e.g. node <path_to_the_skill>/scripts/index.mjs cdp --help). Use this to view the full list of available arguments and their descriptions.
For connector and transport debug logging, see Troubleshooting Reference.
get-console command.get-sources command.take-screenshot command.Remap the function_id:pc_index to the original source code position by provided debug info json file.
Specializes in analyzing Lynx trace data to diagnose performance issues and provide actionable optimization strategies. Key Scenarios: - Loading Performance: Diagnosing slow startup metrics (FCP, FMP, TTI) and white screen issues. - Smoothness Analysis: Investigating root causes for scroll jank, frame drops, and interaction lag. - Regression Detection: Comparing traces to identify performance degradation or verify optimization gains between versions. - Pipeline Deep Dive: Pinpointing bottlenecks in specific rendering stages like Layout, Paint, JS execution, and background threads. - Native Module Analysis: Investigating performance issues related to native module calls.