Individual skill
xberg-extracting-keywords
Use when extracting keywords (YAKE/RAKE) from documents — and, secondarily, when detecting document language or generating embeddings for RAG and search. Covers the keyword config (and its feature gating), `--detect-language`, and the standalone `embed` command with real flags.
plugin/skills/xberg-extracting-keywords/SKILL.md
Source commit 531f2502f8c21c69046ae5d4555c6b714346e574
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 7, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 9,565
- Repository last updated
- Nov 8, 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 · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesSKILL.mdcore · 6,754 bytesindex.mddoc · 572 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: blake3:491d3cbcd4f6128d43e32b39c13d03a023b397f97c71da48ed5a02d6be00ae28
Source-Hash: blake3:1e46ba9bed26e6452c3c82c60b33a2fde65ced1c447fbee44693532abe509487
Schema-Version: v1
-->
# Extracting keywords, language, and embeddings
Use this for the enrichment surface around extraction: statistical keyword
extraction, language detection, and vector embeddings. Keywords and
language detection ride along with extraction and land on the result;
embeddings are produced by a dedicated `embed` command.
