grepai-chunking — Claude Code skill: what it does, how to install
Configures source code chunking for GrepAI embeddings. Helps balance segment size and surrounding context across different programming languages.
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a claude-codeWhat grepai-chunking does
The skill equips the AI agent with strategies to tune code splitting in .grepai/config.yaml. It manages two main variables: size and overlap. These settings define target token counts per chunk and boundary overlaps between adjacent segments.
Splitting follows syntax markers such as empty lines or closing braces. Verbose languages like Java or C# benefit from 768 tokens to capture full methods. Concise languages like Rust or Zig work better with 384 tokens.
Any chunking update requires generating new embeddings. You must delete .grepai/index.gob and trigger grepai watch to rebuild the index.
What it helps with
- tune chunk size for verbose languages like Java or concise ones like Rust
- prevent context loss at function boundaries during semantic search
- reduce vector index bloat caused by excessive overlap
- rebuild the GrepAI index after modifying token settings
Example prompts for the agent
- Configure GrepAI chunking settings for a Go microservice
- Recommend chunk size and overlap in
.grepai/config.yamlfor a Java monolith - Why does GrepAI search return fragmented code snippets instead of full functions?
How to install grepai-chunking
1Skills CLI (Vercel)
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a claude-code2Manually: put the files in place
~/.claude/skills/grepai-chunking/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/grepai-chunking/
1Skills CLI (Vercel)
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a codex2Manually: put the files in place
.agents/skills/grepai-chunking/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a cursor2Manually: put the files in place
.cursor/skills/grepai-chunking/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install yoanbernabeu/grepai-skills grepai-chunking2Manually: put the files in place
.github/skills/grepai-chunking/SKILL.md1Skills CLI (Vercel)
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a gemini-cli2Platform CLI
gemini skills install https://github.com/yoanbernabeu/grepai-skills --path skills/indexing/grepai-chunkingManually: put the files in place
.devin/skills/grepai-chunking/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about grepai-chunking
How to install grepai-chunking in Claude Code?
Run npx skills add yoanbernabeu/grepai-skills --skill grepai-chunking -a claude-code. Alternatively, place the file directly at ~/.claude/skills/grepai-chunking/SKILL.md.
What does grepai-chunking do?
It guides your AI assistant in configuring chunk token limits and overlaps inside .grepai/config.yaml to optimize semantic search accuracy.
How do you apply new chunking settings in GrepAI?
Delete the existing index with rm .grepai/index.gob and run grepai watch to rebuild embeddings with the updated parameters.
Source text
SKILL.md · MIT
---
name: grepai-chunking
description: Configure code chunking in GrepAI. Use this skill to optimize how code is split for embedding.
---
# GrepAI Chunking Configuration
This skill covers how GrepAI splits code files into chunks for embedding, and how to optimize chunking for your codebase.
## When to Use This Skill
- Optimizing search accuracy
- Adjusting for code style (verbose vs. concise)
- Troubleshooting search results
- Understanding how indexing works
## What is Chunking?
Chunking is the process of splitting source files into smaller segments for embedding:
```
┌─────────────────────────────────────┐
│ Large Source File │
│ (1000+ tokens) │
└─────────────────────────────────────┘
↓
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Chunk 1 │ │ Chunk 2 │ │ Chunk 3 │
│ ~512 │ │ ~512 │ │ ~512 │
│ tokens │ │ tokens │ │ tokens │
└─────────┘ └─────────┘ └─────────┘
↓
Each chunk gets
its own embedding
```
## Why Chunking Matters
Embedding models have optimal input sizes:
- **Too large chunks:** Less precise search results
- **Too small chunks:** Lost context, fragmented results
- **Just right:** Good balance of precision and context
## Configuration
### Basic Settings
```yaml
# .grepai/config.yaml
chunking:
size: 512 # Tokens per chunk
overlap: 50 # Overlap between chunks
```
### Understanding Parameters
#### Chunk Size
The target number of tokens per chunk.
| Size | Effect |
|------|--------|
| 256 | More precise, less context |
| 512 | Balanced (default) |
| 1024 | More context, less precise |
#### Overlap
Tokens shared between adjacent chunks. Preserves context at boundaries.
| Overlap | Effect |
|---------|--------|
| 0 | No overlap, may lose context at boundaries |
| 50 | Standard overlap (default) |
| 100 | More context, larger index |
## Visualization
With size=512 and overlap=50:
```
File: auth.go (1000 tokens)
Chunk 1: tokens 1-512
┌────────────────────────────────────┐
│ func Login(user, pass)... │
└────────────────────────────────────┘
↘
50 token overlap
↙
Chunk 2: tokens 463-974
┌────────────────────────────────────┐
│ ...validate credentials... │
└────────────────────────────────────┘
↘
50 token overlap
↙
Chunk 3: tokens 925-1000
┌──────────────┐
│ ...return │
└──────────────┘
```
## Recommended Settings by Language
### Verbose Languages (Java, C#)
```yaml
chunking:
size: 768 # Larger to capture full methods
overlap: 75
```
### Concise Languages (Go, Python)
```yaml
chunking:
size: 512 # Standard size
overlap: 50
```
### Very Concise (Rust, Zig)
```yaml
chunking:
size: 384 # Smaller for precise results
overlap: 40
```
## Recommended Settings by Codebase
### Small Functions (Microservices)
```yaml
chunking:
size: 384 # Capture individual functions
overlap: 40
```
### Large Classes (Monolith)
```yaml
chunking:
size: 768 # Capture more context
overlap: 100
```
### Mixed Codebase
```yaml
chunking:
size: 512 # Balanced default
overlap: 50
```
## How Tokens are Counted
GrepAI uses approximate token counting:
- ~4 characters = 1 token (for English text)
- Code varies based on identifiers and syntax
Example:
```go
func calculateTotal(items []Item) float64 {
total := 0.0
for _, item := range items {
total += item.Price * float64(item.Quantity)
}
return total
}
```
≈ 45 tokens
## Impact on Index Size
Larger overlap = more chunks = larger index:
| Size | Overlap | Chunks per 10K tokens | Index Impact |
|------|---------|----------------------|--------------|
| 512 | 0 | ~20 | Smallest |
| 512 | 50 | ~22 | Standard |
| 512 | 100 | ~24 | +10% |
| 256 | 50 | ~44 | +100% |
## Impact on Search Quality
### Too Small Chunks (size: 128)
```
Query: "authentication middleware"
Result: "...c.AbortWithStatus(401)..."
(Fragment, missing context)
```
### Just Right (size: 512)
```
Query: "authentication middleware"
Result: "func AuthMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
token := c.GetHeader("Authorization")
if token == "" {
c.AbortWithStatus(401)
return
}
// validate token...
}
}"
(Complete function with context)
```
### Too Large Chunks (size: 2048)
```
Query: "authentication middleware"
Result: "// Multiple unrelated functions...
func AuthMiddleware()... (your match)
func LoggingMiddleware()...
func CORSMiddleware()..."
(Too much noise)
```
## Experimentation
### Testing Different Settings
1. Try smaller chunks for more precise results:
```yaml
chunking:
size: 384
overlap: 40
```
2. Re-index:
```bash
rm .grepai/index.gob
grepai watch
```
3. Test with searches:
```bash
grepai search "your query"
```
4. Adjust and repeat until satisfied.
### Comparing Results
Before changing settings, save a search result:
```bash
grepai search "authentication" > before.txt
```
After changing settings and re-indexing:
```bash
grepai search "authentication" > after.txt
diff before.txt after.txt
```
## Chunk Boundaries
GrepAI tries to split at logical boundaries:
1. Empty lines (function/class boundaries)
2. Closing braces
3. Statement ends
This means actual chunk sizes may vary slightly from the target.
## Best Practices
1. **Start with defaults:** 512/50 works well for most codebases
2. **Adjust based on code style:** Verbose = larger, concise = smaller
3. **Test with real queries:** See what your searches return
4. **Re-index after changes:** Must regenerate embeddings
5. **Consider overlap:** Don't set to 0 unless index size is critical
## Common Issues
❌ **Problem:** Search results are too fragmented
✅ **Solution:** Increase chunk size:
```yaml
chunking:
size: 768
```
❌ **Problem:** Search results have too much irrelevant context
✅ **Solution:** Decrease chunk size:
```yaml
chunking:
size: 384
```
❌ **Problem:** Results miss related code at function boundaries
✅ **Solution:** Increase overlap:
```yaml
chunking:
overlap: 100
```
❌ **Problem:** Index is too large
✅ **Solutions:**
- Decrease overlap
- Increase chunk size
- Add more ignore patterns
## Output Format
Chunking status:
```
✅ Chunking Configuration
Size: 512 tokens
Overlap: 50 tokens
Index Statistics:
- Total files: 245
- Total chunks: 1,234
- Avg chunks/file: 5.0
- Avg chunk size: 478 tokens
Recommendations:
- Current settings are balanced
- Consider size: 384 for more precise results
- Consider size: 768 for more context
```
© yoanbernabeu · MIT · yoanbernabeu/grepai-skills