
Grepai Quickstart
Stand up GrepAI on a codebase in minutes so your coding agent can semantic-search the repo locally.
Overview
grepai-quickstart is an agent skill for the Build phase that gets GrepAI installed, indexed, and searching your code in about five minutes.
Install
npx skills add https://github.com/yoanbernabeu/grepai-skills --skill grepai-quickstartWhat is this skill?
- Complete 5-minute path: install GrepAI, Ollama, init, index, search
- Install paths for macOS Homebrew, curl install.sh, and Windows PowerShell
- Local embeddings via Ollama with nomic-embed-text and default .grepai/config.yaml
- Covers first-time setup, new project setup, and demo walkthroughs
- Verify steps for grepai version and Ollama API tags
- 5-minute quickstart walkthrough
- 4 main steps after prerequisites: install GrepAI, install Ollama, init project, start indexing
Adoption & trust: 464 installs on skills.sh; 17 GitHub stars; 1/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
What problem does it solve?
You want semantic search over your repo for agents but do not know the install, Ollama, init, and index sequence for GrepAI.
Who is it for?
First-time GrepAI users, new-repo setup, or a fast demo of local agent-friendly code search.
Skip if: Production multi-user search infrastructure, custom embedding providers beyond the quickstart defaults, or repos you cannot run shell commands on.
When should I use this skill?
First time using GrepAI, need a quick refresher on basic workflow, setting up GrepAI on a new project, or demonstrating GrepAI to someone.
What do I get? / Deliverables
GrepAI is installed, your project is initialized and indexed, and you can run your first semantic search against local embeddings.
- .grepai/config.yaml
- Indexed project store (GOB default)
- Working local semantic search
Recommended Skills
Journey fit
Build is where you wire agent tooling into the project you are actively shipping; quickstart is for getting search/indexing working during development, not launch or growth. Agent-tooling fits install-init-index-search workflows that augment Claude Code, Cursor, or Codex with embeddings over your tree.
How it compares
Onboarding workflow for the GrepAI CLI—not a hosted SaaS search product or an MCP server by itself.
Common Questions / FAQ
Who is grepai-quickstart for?
Solo developers and indie teams who want local semantic code search to support coding agents on their own machine.
When should I use grepai-quickstart?
During Build when you first add GrepAI, clone a new repo to index, or need a refresher on install → Ollama → init → index → search.
Is grepai-quickstart safe to install?
The skill runs install scripts and local services; review the Security Audits panel on this Prism page and inspect install URLs before piping to shell.
SKILL.md
READMESKILL.md - Grepai Quickstart
# 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 | 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 | |