rn-self-feedback — chrome-remote-devtools rn-self-feedback, chrome-remote-devtools, community, ide skills, debugging, debugging-tool, devtools, remote

v1.0.0
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Acerca de este Skill

Ideal para agentes de desarrollo de aplicaciones móviles especializados en React Native, que buscan optimizar su flujo de trabajo de depuración con Maestro MCP y Tauri MCP. Use Maestro MCP and Tauri MCP to run React Native flows and capture Inspector state for self-validation. Use when working on RN/Inspector code and you need to verify changes (run app, run Maestro flows, capture screenshots, then evaluate results).

# Core Topics

chrome-remote-devtools debugging debugging-tool devtools remote
ohah ohah
[7]
[0]
Updated: 2/21/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
7/11
Quality Score
38
Canonical Locale
en
Detected Body Locale
en

Ideal para agentes de desarrollo de aplicaciones móviles especializados en React Native, que buscan optimizar su flujo de trabajo de depuración con Maestro MCP y Tauri MCP. Use Maestro MCP and Tauri MCP to run React Native flows and capture Inspector state for self-validation. Use when working on RN/Inspector code and you need to verify changes (run app, run Maestro flows, capture screenshots, then evaluate results).

¿Por qué usar esta habilidad?

Permite a los agentes verificar los cambios de código de React Native y capturar el estado utilizando Maestro MCP y Tauri MCP, lo que facilita la depuración y prueba eficientes de las modificaciones del código del Inspector y proporciona una retroalimentación automática sobre el comportamiento del código.

Mejor para

Ideal para agentes de desarrollo de aplicaciones móviles especializados en React Native, que buscan optimizar su flujo de trabajo de depuración con Maestro MCP y Tauri MCP.

↓ Casos de uso accionables for rn-self-feedback

Depuración de modificaciones de código de React Native o Inspector
Verificación del comportamiento después de cambiar paquetes/react-native-inspector
Captura del estado y evaluación de resultados para cambios de código de RN

! Seguridad y limitaciones

  • Requiere la configuración de Maestro MCP y Tauri MCP
  • Específico para la depuración de código de React Native y Inspector

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

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Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is rn-self-feedback?

Ideal para agentes de desarrollo de aplicaciones móviles especializados en React Native, que buscan optimizar su flujo de trabajo de depuración con Maestro MCP y Tauri MCP. Use Maestro MCP and Tauri MCP to run React Native flows and capture Inspector state for self-validation. Use when working on RN/Inspector code and you need to verify changes (run app, run Maestro flows, capture screenshots, then evaluate results).

How do I install rn-self-feedback?

Run the command: npx killer-skills add ohah/chrome-remote-devtools. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for rn-self-feedback?

Key use cases include: Depuración de modificaciones de código de React Native o Inspector, Verificación del comportamiento después de cambiar paquetes/react-native-inspector, Captura del estado y evaluación de resultados para cambios de código de RN.

Which IDEs are compatible with rn-self-feedback?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for rn-self-feedback?

Requiere la configuración de Maestro MCP y Tauri MCP. Específico para la depuración de código de React Native y Inspector.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add ohah/chrome-remote-devtools. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use rn-self-feedback immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

rn-self-feedback

Install rn-self-feedback, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

RN Self-Feedback (Maestro + Tauri MCP)

When you change React Native or Inspector code and need to verify behavior, use Maestro MCP and Tauri MCP to run the app, run flows, and capture state—then evaluate the results yourself.

When to use

  • After changing packages/react-native-inspector or related RN/Inspector code.
  • When the user or context implies "verify this" or "check if it works" for RN.
  • When you want to give yourself feedback on whether a change behaves correctly.

Prerequisites

  • MCP setup: MCP is configured so the tauri and maestro servers use the correct mise path. If this repo provides it, run bun run setup-mcp once per machine.
  • Tauri MCP: Inspector (Tauri) app running in debug (bun run dev:inspector:tauri) so Tauri MCP can connect.
  • Maestro MCP: Maestro available via mise (.mise.toml); Maestro MCP enabled in Cursor.

Workflow

  1. Run / drive the RN app

    • Use Maestro MCP to run flows or start the app as needed (e.g. maestro run ... or equivalent MCP tools). Check available Maestro MCP tools for run, tap, assert, etc.

  2. Capture Inspector / UI state

    • Use Tauri MCP to take a screenshot of the Inspector (e.g. "Take a screenshot of my app") or to interact (click, type) if needed.

  3. Evaluate

    • From the screenshot or flow result, decide: does the change work as intended? Note any failures or UI mismatches and suggest fixes.

Notes

  • MCP tools are provided by the configured maestro and tauri servers in your MCP configuration. Call them when you need to run or inspect the RN/Inspector stack.
  • If Tauri MCP cannot connect, confirm Inspector is running with bun run dev:inspector:tauri (debug build).
  • If Maestro MCP fails, ensure MCP is configured (e.g. run bun run setup-mcp if available) and Maestro is installed via mise.

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