AgentStack
SKILL verified MIT Self-run

Grepai Chunking

skill-yoanbernabeu-grepai-skills-grepai-chunking · by yoanbernabeu

Configure code chunking in GrepAI. Use this skill to optimize how code is split for embedding.

No reviews yet
0 installs
7 views
0.0% view→install

Install

$ agentstack add skill-yoanbernabeu-grepai-skills-grepai-chunking

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

Are you the author of Grepai Chunking? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

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

# .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#)

chunking:
  size: 768    # Larger to capture full methods
  overlap: 75

Concise Languages (Go, Python)

chunking:
  size: 512    # Standard size
  overlap: 50

Very Concise (Rust, Zig)

chunking:
  size: 384    # Smaller for precise results
  overlap: 40

Recommended Settings by Codebase

Small Functions (Microservices)

chunking:
  size: 384    # Capture individual functions
  overlap: 40

Large Classes (Monolith)

chunking:
  size: 768    # Capture more context
  overlap: 100

Mixed Codebase

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:

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:
chunking:
  size: 384
  overlap: 40
  1. Re-index:
rm .grepai/index.gob
grepai watch
  1. Test with searches:
grepai search "your query"
  1. Adjust and repeat until satisfied.

Comparing Results

Before changing settings, save a search result:

grepai search "authentication" > before.txt

After changing settings and re-indexing:

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:

chunking:
  size: 768

Problem: Search results have too much irrelevant context ✅ Solution: Decrease chunk size:

chunking:
  size: 384

Problem: Results miss related code at function boundaries ✅ Solution: Increase overlap:

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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet — be the first.

Versions

  • v0.1.0 Imported from the upstream source.