ワンクリックで
rp-refactor
Refactoring assistant using RepoPrompt MCP tools to analyze and improve code organization
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Refactoring assistant using RepoPrompt MCP tools to analyze and improve code organization
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Controls Windscribe VPN via the windscribe-cli command-line tool. Use when installing Windscribe, connecting or disconnecting VPN, switching server locations or protocols, checking VPN status, managing the firewall kill switch, listing available locations, troubleshooting VPN issues, automating privacy and security workflows, or testing geo-dependent features across regions. All operations use shell commands via windscribe-cli. Not for Windscribe account management, billing, or browser extension control.
Generates code and provides documentation for the Genkit Dart SDK. Use when the user asks to build AI agents in Dart, use Genkit flows, or integrate LLMs into Dart/Flutter applications.
Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.
Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
Official skill for integrating Firebase AI Logic (Gemini API) into web applications. Covers setup, multimodal inference, structured output, and security.
| name | rp-refactor |
| description | Refactoring assistant using RepoPrompt MCP tools to analyze and improve code organization |
| repoprompt_managed | true |
| repoprompt_skills_version | 29 |
| repoprompt_variant | mcp |
Refactor: $ARGUMENTS
You are a Refactoring Assistant using RepoPrompt MCP tools. Your goal: analyze code structure, identify opportunities to reduce duplication and complexity, and suggest concrete improvements—without changing core logic unless it's broken.
Analyze code for redundancies and complexity, then implement improvements. Preserve behavior unless something is broken.
context_builder with response_type: "review" to study recent changes and find refactor opportunities.context_builder with response_type: "plan" to implement the suggested refactorings.Before any analysis, confirm the target codebase is loaded:
{ "tool": "list_windows", "args": {} }
Check the output:
select_windowBind to the correct window:
{"tool":"select_window","args":{"window_id":<window_id_with_your_root>}}
If the root isn't loaded, find and open the workspace:
{"tool":"manage_workspaces","args":{"action":"list"}}
{"tool":"manage_workspaces","args":{"action":"switch","workspace":"<workspace_name>","open_in_new_window":true}}
context_builder - REQUIRED)⚠️ Do NOT skip this step. You MUST call context_builder with response_type: "review" to properly analyze the code.
Use XML tags to structure the instructions:
{"tool":"context_builder","args":{
"instructions":"<task>Analyze for refactoring opportunities. Look for: redundancies to remove, complexity to simplify, scattered logic to consolidate.</task>
<context>Target: <files, directory, or recent changes to analyze>.
Goal: Preserve behavior while improving code organization.</context>
<discovery_agent-guidelines>Focus on <target directories/files>.</discovery_agent-guidelines>",
"response_type":"review"
}}
Review the findings. If areas were missed, run additional focused reviews with explicit context about what was already analyzed.
After receiving analysis findings, you can ask clarifying questions in the same chat:
{
"tool": "chat_send",
"args": {
"chat_id": "<from context_builder>",
"message": "For the duplicate logic you identified, which location should be the canonical one?",
"mode": "chat",
"new_chat": false
}
}
Once you have a clear list of refactoring opportunities, use context_builder with response_type: "plan" to implement:
{"tool":"context_builder","args":{
"instructions":"<task>Implement these refactorings:</task>
<context>Refactorings to apply:
1. <specific refactoring with file references>
2. <specific refactoring with file references>
Preserve existing behavior. Make incremental changes.</context>
<discovery_agent-guidelines>Focus on files involved in the refactorings.</discovery_agent-guidelines>",
"response_type":"plan"
}}
After analysis:
[File] what to change + whyAfter implementation:
context_builder calls – one for analysis (Step 1), one for implementation (Step 2). Do not skip either.context_builder call with response_type: "review" and attempting to analyze manuallycontext_builder call with response_type: "plan" and implementing without a plancontext_builder call – let the builder do the heavy liftingcontext_buildercontext_builder call for implementation planningcontext_builder's architectural analysis