rag-first — for Claude Code rag-first, dev-rag, community, for Claude Code, ide skills, mcp__devrag__search, Codebase, Search, Before, Explore

v1.0.0

关于此技能

适用场景: rag-first codebase search. 本地化技能摘要: # RAG-First Codebase Search Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first. Claude Code, Cursor, and Windsurf workflows.

功能特性

RAG-First Codebase Search
Call mcp devrag search with your query.
Evaluate the results:
For "where is X defined?" questions, RAG's AST-aware code chunks often give better results than
If the DevRAG MCP server is not available (tool call fails), fall back to direct exploration

# 核心主题

tomharris tomharris
[1]
[0]
更新于: 4/17/2026

技能概览

先看适用场景、限制条件和安装路径,再决定是否继续深入。

适用场景: rag-first codebase search. 本地化技能摘要: # RAG-First Codebase Search Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first. Claude Code, Cursor, and Windsurf workflows.

核心价值

推荐说明: rag-first helps agents rag-first codebase search. RAG-First Codebase Search Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first.

适用 Agent 类型

适用场景: rag-first codebase search.

赋予的主要能力 · rag-first

适用任务: RAG-First Codebase Search
适用任务: Call mcp devrag search with your query
适用任务: Evaluate the results:

! 使用限制与门槛

  • 限制说明: Requires repository-specific context from the skill documentation
  • 限制说明: Works best when the underlying tools and dependencies are already configured

关于来源内容

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

实验室 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

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

rag-first 是什么?

适用场景: rag-first codebase search. 本地化技能摘要: # RAG-First Codebase Search Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first. Claude Code, Cursor, and Windsurf workflows.

如何安装 rag-first?

运行命令:npx killer-skills add tomharris/dev-rag。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

rag-first 适用于哪些场景?

典型场景包括:适用任务: RAG-First Codebase Search、适用任务: Call mcp devrag search with your query、适用任务: Evaluate the results:。

rag-first 支持哪些 IDE 或 Agent?

该技能兼容 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。可使用 Killer-Skills CLI 一条命令通用安装。

rag-first 有哪些限制?

限制说明: Requires repository-specific context from the skill documentation;限制说明: Works best when the underlying tools and dependencies are already configured。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add tomharris/dev-rag。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    rag-first 已启用,可立即在当前项目中调用。

! 来源说明

此页面仍可作为安装与查阅参考。继续使用前,请结合上方适用场景、限制条件和上游仓库说明一起判断。

Upstream Repository Material

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

rag-first

# RAG-First Codebase Search Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first. This AI agent skill

SKILL.md
Readonly
Upstream Repository Material
The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

RAG-First Codebase Search

Before using Grep, Glob, Explore agents, or other codebase exploration tools, ALWAYS search DevRAG first. The RAG index has semantic understanding of code structure, PR history, and documentation that keyword search misses.

Process

  1. Formulate a search query from the user's question. Use natural language — DevRAG uses semantic search, not keyword matching. Include key terms but phrase it as a question or description.

  2. Call mcp__devrag__search with your query.

  3. Evaluate the results:

    • If results are relevant and sufficient — present them grouped by source type (code, PR, doc). Show file paths, snippets, PR numbers, and document sections.
    • If results are partial — use them as a starting point, then supplement with targeted Grep/Glob/Read on specific files or patterns identified from the RAG results.
    • If results are empty or irrelevant — state "RAG results were limited for this query, falling back to direct codebase exploration" and proceed with Grep/Glob/Read/Explore as normal.
  4. Combine sources — when RAG gives you file paths and context, use Read to pull in the full current code. RAG results may be from a previous index, so always verify against current files.

Key Guidelines

  • DevRAG searches across four collections: code chunks, PR diffs, PR discussions, and documents. A single query searches all relevant collections.
  • For "why did this change?" questions, RAG is especially powerful — it has PR history and review comments that Grep cannot find.
  • For "where is X defined?" questions, RAG's AST-aware code chunks often give better results than grep patterns.
  • Do NOT skip RAG even for seemingly simple lookups — the semantic search may surface related context you wouldn't have found with keywords.
  • If the DevRAG MCP server is not available (tool call fails), fall back to direct exploration without retrying.

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