grepai-search-basics▌
yoanbernabeu/grepai-skills · updated Apr 8, 2026
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Semantic code search by meaning rather than exact text strings.
- ›Searches code by intent and concept similarity using embeddings, returning ranked results with relevance scores (0.0–1.0)
- ›Requires GrepAI initialization, an active index created via grepai watch , and a running embedding provider like Ollama
- ›Supports natural language queries describing behavior or intent; 3–7 word phrases work best, with results limited via --limit flag
- ›Interprets scores: 0.90+ excellent match, 0.80–0
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
- GrepAI initialized (
grepai init) - Index created (
grepai watch) - 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
- Use English: Models are trained on English
- Be specific: "JWT token validation" vs "validation"
- Describe intent: What the code DOES, not what it's called
- Use 3-7 words: Enough context, not too verbose
- 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 watchif 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
How to use grepai-search-basics on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add grepai-search-basics
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches grepai-search-basics from GitHub repository yoanbernabeu/grepai-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate grepai-search-basics. Access the skill through slash commands (e.g., /grepai-search-basics) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★28 reviews- ★★★★★Liam Garcia· Dec 24, 2024
Registry listing for grepai-search-basics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Chaitanya Patil· Dec 12, 2024
grepai-search-basics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Li Sharma· Nov 15, 2024
Useful defaults in grepai-search-basics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Piyush G· Nov 3, 2024
I recommend grepai-search-basics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Oct 22, 2024
Useful defaults in grepai-search-basics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mei Kim· Oct 6, 2024
I recommend grepai-search-basics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Sep 13, 2024
grepai-search-basics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Kiara Wang· Sep 1, 2024
Registry listing for grepai-search-basics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kiara Jackson· Aug 20, 2024
grepai-search-basics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dhruvi Jain· Aug 4, 2024
Solid pick for teams standardizing on skills: grepai-search-basics is focused, and the summary matches what you get after install.
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