Grepai Quickstart
Get started with GrepAI in 5 minutes. Use this skill for a complete walkthrough from installation to first search.
- Skill ID
- yoanbernabeu/grepai-skills/grepai-quickstart
- Publisher
- yoanbernabeu
- Repository
- grepai-skills
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
yoanbernabeu/grepai-skills/grepai-quickstartInstalls these files- SKILL.md
What this skill tells the agent
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
brew install yoanbernabeu/tap/grepaiLinux/macOS (Alternative)
curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | shWindows
irm https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.ps1 | iexVerify: grepai version
Step 2: Install Ollama (Local Embeddings)
macOS
brew install ollama
ollama serve &
ollama pull nomic-embed-textLinux
curl -fsSL https://ollama.com/install.sh | sh
ollama serve &
ollama pull nomic-embed-textVerify: curl http://localhost:11434/api/tags
Step 3: Initialize Your Project
Navigate to your project and initialize GrepAI:
cd /path/to/your/project
grepai initThis creates .grepai/config.yaml with default settings:
- Ollama as embedding provider
nomic-embed-textmodel- GOB file storage
- Standard ignore patterns
Step 4: Start Indexing
Start the watch daemon to index your code:
grepai watchWhat happens:
- Scans all source files (respects
.gitignore) - Chunks code into ~512 token segments
- Generates embeddings via Ollama
- 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:
# Start in background
grepai watch --background
# Check status
grepai watch --status
# Stop when done
grepai watch --stopStep 5: Search Your Code
Now search semantically:
# Basic search
grepai search "authentication flow"
# Limit results
grepai search "error handling" --limit 5
# JSON output for scripts
grepai search "database queries" --jsonExample 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:
# 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 3Complete Workflow Summary
# 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
| Command | Purpose |
|---|---|
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:
- Configure embeddings: See
grepai-embeddings-*skills - Setup storage: See
grepai-storage-*skills - Advanced search: See
grepai-search-*skills - 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"More from yoanbernabeu
Use this skill in a project
Open any RiverX project, search the Skills panel for yoanbernabeu/grepai-skills/grepai-quickstart, and install it in one click.
