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grepai-search-basicsgrepai 搜索基础知识

Agent Skill

grepai-search-basics 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,992

周安装

566

GitHub Stars

16

下载量

4,392
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:grepai-search-basics(grepai 搜索基础知识)
来源仓库:https://github.com/yoanbernabeu/grepai-skills
仓库路径:skills/grepai-search-basics
安装命令:
npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-search-basics
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-search-basics

简介

通过含义而不是精确的文本字符串进行语义代码搜索。

  • 使用嵌入按意图和概念相似性搜索代码,返回具有相关性得分 (0.0–1.0) 的排名结果
  • 需要 GrepAI 初始化,通过 grepai watch 创建的活动索引,以及像 Ollama 这样正在运行的嵌入提供商
  • 支持描述行为或意图的自然语言查询; 3-7 个单词的短语效果最好,通过 --limit 限制结果
  • 旗帜
  • 解释分数:0.90+ 优秀匹配、0.80–0.89 良好匹配、0.70–0.79 相关、0.60 以下弱匹配

SKILL.md

GrepAI Search Basics

This skill covers the fundamentals of semantic code search with GrepAI.

When to Use This Skill

  • Learning GrepAI search
  • Performing basic code searches
  • Understanding semantic vs. text search
  • Interpreting search results

Prerequisites

  1. GrepAI initialized (grepai init)
  2. Index created (grepai watch)
  3. Embedding provider running (Ollama, etc.)

What is Semantic Search?

Unlike traditional text search (grep, ripgrep), GrepAI searches by meaning:

TypeHow it WorksExample
Text searchExact string match"login" → finds "login"
Semantic searchMeaning similarity"authenticate user" → finds login, auth, signin code

Basic Search Command

grepai search "your query here"

Example

grepai search "user authentication flow"

Output:

Score: 0.89 | src/auth/middleware.go:15-45
──────────────────────────────────────────
func AuthMiddleware() gin.HandlerFunc {
    return func(c *gin.Context) {
        token := c.GetHeader("Authorization")
        if token == "" {
            c.AbortWithStatus(401)
            return
        }
        claims, err := ValidateToken(token)
        if err != nil {
            c.AbortWithStatus(401)
            return
        }
        c.Set("user", claims.UserID)
        c.Next()
    }
}

Score: 0.82 | src/auth/jwt.go:23-55
──────────────────────────────────────────
func ValidateToken(tokenString string) (*Claims, error) {
    token, err := jwt.Parse(tokenString, func(t *jwt.Token) (interface{}, error) {
        return []byte(secretKey), nil
    })
    if err != nil {
        return nil, err
    }
    if claims, ok := token.Claims.(*Claims); ok && token.Valid {
        return claims, nil
    }
    return nil, errors.New("invalid token")
}

Score: 0.76 | src/handlers/login.go:10-35
──────────────────────────────────────────
func HandleLogin(c *gin.Context) {
    var req LoginRequest
    if err := c.ShouldBindJSON(&req); err != nil {
        c.JSON(400, gin.H{"error": "invalid request"})
        return
    }
    user, err := userService.Authenticate(req.Email, req.Password)
    // ...
}

Understanding Results

Result Format

Score: 0.89 | src/auth/middleware.go:15-45
──────────────────────────────────────────
[code content]
ComponentMeaning
ScoreSimilarity (0.0 to 1.0, higher = more relevant)
File pathLocation of the code
Line numbersStart-end lines of the chunk
ContentThe actual code

Score Interpretation

ScoreMeaning
0.90+Excellent match
0.80-0.89Good match
0.70-0.79Related
0.60-0.69Loosely related
<0.60Weak match

Limiting Results

By default, GrepAI returns 10 results. Adjust with --limit:

# Get only top 3 results
grepai search "database queries" --limit 3

# Get more results
grepai search "error handling" --limit 20

Checking Index Status

Before searching, verify your index:

grepai status

Output:

✅ GrepAI Status

   Index:
   - Files: 245
   - Chunks: 1,234
   - Last updated: 2 minutes ago

   Ready for search.

Search vs Grep Comparison

Traditional grep

grep -r "authenticate" .
  • Finds exact text "authenticate"
  • Misses synonyms (login, signin, auth)
  • Returns all matches, unranked

GrepAI search

grepai search "authenticate user credentials"
  • Finds semantically similar code
  • Includes related concepts
  • Results ranked by relevance

What Makes a Good Query

Good Queries ✅

Describe the intent or behavior:

grepai search "validate user credentials"
grepai search "handle HTTP request errors"
grepai search "connect to the database"
grepai search "send email notification"
grepai search "parse JSON configuration"

Less Effective Queries ❌

Too short or generic:

grepai search "auth"           # Too vague
grepai search "function"       # Too generic
grepai search "getUserById"    # Exact name (use grep)

Natural Language Queries

GrepAI understands natural language:

# Ask questions
grepai search "how are users authenticated"
grepai search "where is the database connection configured"

# Describe behavior
grepai search "code that sends emails to users"
grepai search "functions that validate input data"

Multiple Words vs Phrases

Both work, but phrases often get better results:

# Multiple words (OR-like behavior)
grepai search "login password validation"

# Phrase (describes specific intent)
grepai search "validate user login credentials"

Quick Tips

  1. Use English: Models are trained on English
  2. Be specific: "JWT token validation" vs "validation"
  3. Describe intent: What the code DOES, not what it's called
  4. Use 3-7 words: Enough context, not too verbose
  5. Iterate: Refine query based on results

Common Search Patterns

Finding Entry Points

grepai search "main entry point"
grepai search "application startup"
grepai search "HTTP server initialization"

Finding Error Handling

grepai search "error handling and logging"
grepai search "exception handling"
grepai search "error response to client"

Finding Data Access

grepai search "database query execution"
grepai search "fetch user from database"
grepai search "save data to storage"

Finding Business Logic

grepai search "calculate order total"
grepai search "process payment transaction"
grepai search "validate business rules"

Troubleshooting

Problem: No results ✅ Solutions:

  • Check index exists: grepai status
  • Run grepai watch if index is empty
  • Simplify query

Problem: Irrelevant results ✅ Solutions:

  • Be more specific
  • Use different words
  • Check if code exists in the codebase

Problem: Missing expected code ✅ Solutions:

  • Check if file is ignored in config
  • Ensure file extension is supported
  • Re-index: rm.grepai/index.gob && grepai watch

Output Format

Successful basic search:

Query: "user authentication flow"
Results: 5 matches

Score: 0.89 | src/auth/middleware.go:15-45
──────────────────────────────────────────
[relevant code...]

Score: 0.82 | src/auth/jwt.go:23-55
──────────────────────────────────────────
[relevant code...]

[additional results...]

Tip: Use --limit to adjust number of results
     Use --json for machine-readable output

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.28%
按下载量换算1,549

Claude

27.23%
按下载量换算1,196

Cursor

20.43%
按下载量换算897

Gemini CLI

8.79%
按下载量换算386

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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