Individual skill
xberg-chunking
Use when splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone `chunk` command.
plugin/.cursor-plugin/skills/xberg-chunking/SKILL.md
Source commit 531f2502f8c21c69046ae5d4555c6b714346e574
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 9,567
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- text-extraction Repository topic
- document-intelligence Repository topic
- metadata-extraction Repository topic
- pdf-extraction Repository topic
- python Repository topic
- rag Repository topic
- table-extraction Repository topic
- tesseract Repository topic
- ffi Repository topic
- golang Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesSKILL.mdcore · 6,331 bytesindex.mddoc · 489 bytesreferences/advanced-features.mddoc · 18,454 bytesreferences/cli-reference.mddoc · 12,774 bytesreferences/configuration.mddoc · 33,832 bytesreferences/nodejs-api.mddoc · 13,442 bytesreferences/other-bindings.mddoc · 8,744 bytesreferences/python-api.mddoc · 31,582 bytesreferences/rust-api.mddoc · 12,677 bytesreferences/supported-formats.mddoc · 20,572 bytes
Read excerpt
<!--
AI-RULEZ :: GENERATED FILE — DO NOT EDIT
Content-Hash: blake3:aaaffebaf030b1c214ffc0a869f0a63366360a5a568638f6996b98e75901d121
Source-Hash: blake3:1e46ba9bed26e6452c3c82c60b33a2fde65ced1c447fbee44693532abe509487
Schema-Version: v1
-->
# Chunking
Use this when feeding documents into an LLM context window or a vector
store. Xberg chunks two ways: inline during extraction (chunks land on
each document's `chunks` field), or standalone via the `chunk` command for text you
already have. Sizing is character-based by default, or token-based when a
tokenizer model is supplied.