grepai-search-basics

name	grepai-search-basics
description	Basic semantic code search with GrepAI. Use this skill to learn fundamental search commands and concepts.

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:

Type	How it Works	Example
Text search	Exact string match	"login" → finds "login"
Semantic search	Meaning 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]

Component	Meaning
Score	Similarity (0.0 to 1.0, higher = more relevant)
File path	Location of the code
Line numbers	Start-end lines of the chunk
Content	The actual code

Score Interpretation

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