grepai-quickstart

Q: How do I install grepai-quickstart?

Run npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-quickstart in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/grepai-quickstart/ (personal) or .claude/skills/grepai-quickstart/ (project).

by yoanbernabeu

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

Installs: 594
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-quickstart

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads grepai-quickstart automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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/grepai

Linux/macOS (Alternative)

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

Windows

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

Verify: grepai version

Step 2: Install Ollama (Local Embeddings)

macOS

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

Linux

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:

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:

grepai watch

What 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 --stop

Step 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" --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:

# 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

# 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"

FAQ

What does the grepai-quickstart skill do?

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

How do I install grepai-quickstart?

Run npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-quickstart in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/grepai-quickstart/ (personal) or .claude/skills/grepai-quickstart/ (project).

Which AI agents can use grepai-quickstart?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is grepai-quickstart safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains grepai-quickstart?

It is published by yoanbernabeu in yoanbernabeu/grepai-skills. It has 594 recorded installs.

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grepai-quickstart

Install

Install

Describe the task

Review the result

SKILL.md

GrepAI Quickstart

When to Use This Skill

Prerequisites

Step 1: Install GrepAI

macOS

Linux/macOS (Alternative)

Windows

Step 2: Install Ollama (Local Embeddings)

macOS

Linux

Step 3: Initialize Your Project

Step 4: Start Indexing

Background Mode

Step 5: Search Your Code

Example Output

Step 6: Analyze Call Graphs (Optional)

Complete Workflow Summary

Quick Command Reference

Search Tips

Next Steps

Output Format

FAQ

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