grepai-quickstart

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Translated

Get started with GrepAI in 5 minutes. Use this skill for a complete walkthrough from installation to first search.

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Sourceyoanbernabeu/grepai-skills
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NPX Install

npx skill4agent add yoanbernabeu/grepai-skills grepai-quickstart

Tags

Translated version includes tags in frontmatter
grepai-quickstartsemantic-code-searchollama-integrationcode-indexingdeveloper-tools

SKILL.md Content

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GrepAI Quickstart

This skill provides a complete walkthrough to get GrepAI running and searching your code in 5 minutes.

When to Use This Skill

  • First time using GrepAI
  • Need a quick refresher on basic workflow
  • Setting up GrepAI on a new project
  • Demonstrating GrepAI to someone

Prerequisites

  • Terminal access
  • A code project to index

Step 1: Install GrepAI

macOS

bash
brew install yoanbernabeu/tap/grepai

Linux/macOS (Alternative)

bash
curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh

Windows

powershell
irm https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.ps1 | iex
Verify: 
grepai version

Step 2: Install Ollama (Local Embeddings)

macOS

bash
brew install ollama
ollama serve &
ollama pull nomic-embed-text

Linux

bash
curl -fsSL https://ollama.com/install.sh | sh
ollama serve &
ollama pull nomic-embed-text
Verify: 
curl http://localhost:11434/api/tags

Step 3: Initialize Your Project

Navigate to your project and initialize GrepAI:
bash
cd /path/to/your/project
grepai init
This creates 
.grepai/config.yaml
with default settings:
  • Ollama as embedding provider
  • nomic-embed-text
    model
  • GOB file storage
  • Standard ignore patterns

Step 4: Start Indexing

Start the watch daemon to index your code:
bash
grepai watch
What happens:
  1. Scans all source files (respects 
    .gitignore
    )
  2. Chunks code into ~512 token segments
  3. Generates embeddings via Ollama
  4. Stores vectors in 
    .grepai/index.gob
First indexing output:
🔍 GrepAI Watch
   Scanning files...
   Found 245 files
   Processing chunks...
   ████████████████████████████████ 100%
   Indexed 1,234 chunks
   Watching for changes...

Background Mode

For long-running projects:
bash
# Start in background
grepai watch --background

# Check status
grepai watch --status

# Stop when done
grepai watch --stop

Step 5: Search Your Code

Now search semantically:
bash
# Basic search
grepai search "authentication flow"

# Limit results
grepai search "error handling" --limit 5

# JSON output for scripts
grepai search "database queries" --json

Example 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
        }
        // Validate JWT token...
    }
}

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
    })
    // ...
}

Step 6: Analyze Call Graphs (Optional)

Trace function relationships:
bash
# Who calls this function?
grepai trace callers "Login"

# What does this function call?
grepai trace callees "ProcessPayment"

# Full dependency graph
grepai trace graph "ValidateToken" --depth 3

Complete Workflow Summary

bash
# 1. Install (once)
brew install yoanbernabeu/tap/grepai
brew install ollama && ollama serve & && ollama pull nomic-embed-text

# 2. Setup project (once per project)
cd /your/project
grepai init

# 3. Index (run in background)
grepai watch --background

# 4. Search (as needed)
grepai search "your query here"

# 5. Trace (as needed)
grepai trace callers "FunctionName"

Quick Command Reference

CommandPurpose
grepai init
Initialize project config
grepai watch
Start indexing daemon
grepai watch --background
Run daemon in background
grepai watch --status
Check daemon status
grepai watch --stop
Stop daemon
grepai search "query"
Semantic search
grepai search --json
JSON output
grepai trace callers "fn"
Find callers
grepai trace callees "fn"
Find callees
grepai status
Index statistics
grepai version
Show version

Search Tips

Be descriptive, not literal:
  • ✅ "user authentication and session management"
  • ❌ "auth"
Describe intent:
  • ✅ "where errors are logged to the console"
  • ❌ "console.error"
Use English:
  • Models are trained primarily on English text
  • Works best with English queries

Next Steps

After mastering the basics:
  1. Configure embeddings: See 
    grepai-embeddings-*
    skills
  2. Setup storage: See 
    grepai-storage-*
    skills
  3. Advanced search: See 
    grepai-search-*
    skills
  4. MCP integration: See 
    grepai-mcp-*
    skills

Output Format

Successful quickstart:
✅ GrepAI Quickstart Complete

   Project: /path/to/your/project
   Files indexed: 245
   Chunks created: 1,234
   Embedder: Ollama (nomic-embed-text)
   Storage: GOB (local file)

   Try these searches:
   - grepai search "main entry point"
   - grepai search "database connection"
   - grepai search "error handling"