Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yoanbernabeu/grepai-skills --skill grepai-chunkinggit clone --depth 1 https://github.com/yoanbernabeu/grepai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-chunking)<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-chunking"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-chunking/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-chunking"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-chunking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.01746 |
| Opus 5 | $0.00014 | $0.00873 |
| Sonnet 5 | $0.00005 | $0.00349 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
grepai-chunking scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 │
└──────────────┘
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 330 lines · 27 tokens per session scan A 0ad76952def6
grepai-chunking is a skill published in the GitHub repository yoanbernabeu/grepai-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 27 tokens to every session and 1,746 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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