Indexion Segment
- 4.9k installs
- 1 repo stars
- Updated July 20, 2026
- trkbt10/indexion-skills
indexion-segment is an agent skill for splitting text into contextual segments via indexion segment CLI strategies for RAG and embeddings.
About
The indexion-segment skill teaches agents to split text into contextual chunks for RAG and embedding pipelines with the indexion segment CLI. Default window strategy uses sliding window divergence detection; alternatives include TF-IDF topic change detection, punctuation and sentence boundaries, and hybrid NCD plus TF-IDF weighting for mixed-content documents. Operators tune granularity via min-size, max-size, target-size, threshold, window-size, and adaptive threshold flags, then emit prefixed segment files to an output directory. Invoke when users need document chunking for retrieval, meaningful section splits, or sub-document similarity prep. Workflow runs default segmentation first, adjusts threshold and target-size for chunk length, then enables hybrid mode with ncd-weight and tfidf-weight when single strategies underperform. CLI flags cover --strategy=tfidf, --strategy=punctuation, --hybrid, --prefix, and custom divergence thresholds so downstream vector indexes receive consistently sized, context-aware segments.
- Splits text with window, TF-IDF, punctuation, or hybrid NCD plus TF-IDF strategies.
- Tunes chunk size via min-size, max-size, target-size, threshold, and window-size flags.
- Writes prefixed segment files to an output directory for embedding pipelines.
- Adaptive threshold mode adjusts divergence sensitivity on heterogeneous documents.
- Targets RAG chunking, section extraction, and sub-document similarity preparation.
Indexion Segment by the numbers
- 4,897 all-time installs (skills.sh)
- +1 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #158 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 4, 2026 (Skillselion catalog sync)
indexion-segment capabilities & compatibility
- Capabilities
- window divergence segmentation with adaptive thr · tf idf and punctuation boundary strategies · hybrid ncd plus tf idf weighting for mixed conte · configurable min, max, and target segment sizes · prefixed multi file segment output directories
- Use cases
- documentation · orchestration · research
- Platforms
- macOS · Linux · Windows
- Runs
- Runs locally
What indexion-segment says it does
User needs to chunk text for RAG or embedding pipelines
Split text into contextual segments using divergence-based, TF-IDF, or punctuation strategies.
Use `--hybrid` mode for better accuracy on mixed-content documents
npx skills add https://github.com/trkbt10/indexion-skills --skill indexion-segmentAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 4.9k |
|---|---|
| repo stars | ★ 1 |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 20, 2026 |
| Repository | trkbt10/indexion-skills ↗ |
How do I chunk documents into meaningful segments for RAG or embedding pipelines?
Split documents into contextual text segments for RAG and embedding pipelines using indexion segment CLI strategies.
Who is it for?
Teams preparing document chunks for RAG, vector search, or sub-document similarity analysis with indexion.
Skip if: Skip when you only need wiki page maintenance or code-to-doc reconciliation without text segmentation.
When should I use this skill?
User needs to chunk text for RAG, split documents into sections, or segment files for embedding pipelines.
What you get
Segment files sized and split by chosen strategy, ready for embedding and retrieval indexes.
- Chunked text files in output directory
- Segmentation strategy selection for pipeline config
By the numbers
- Supports 4 segmentation strategies: window, TF-IDF, punctuation, and hybrid
Files
indexion segment
Split text into contextual segments using divergence-based, TF-IDF, or punctuation strategies.
When to Use
- User needs to chunk text for RAG or embedding pipelines
- User wants to split a document into meaningful sections
- User asks to segment text for processing
- Preparing text for similarity analysis at sub-document level
Usage
# Default window divergence strategy
indexion segment <input-file> <output-dir>
# TF-IDF based segmentation
indexion segment --strategy=tfidf <input-file> <output-dir>
# Punctuation-based segmentation
indexion segment --strategy=punctuation <input-file> <output-dir>
# Custom segment sizes
indexion segment --min-size=200 --max-size=3000 --target-size=800 document.txt output/
# Custom divergence threshold
indexion segment --threshold=0.5 document.txt output/
# Adaptive threshold mode (default)
indexion segment --adaptive document.txt output/
# Hybrid NCD+TF-IDF mode
indexion segment --hybrid --ncd-weight=0.6 --tfidf-weight=0.4 document.txt output/
# Custom window size
indexion segment --window-size=5 document.txt output/
# Custom output prefix
indexion segment --prefix=chunk document.txt output/Options
| Option | Default | Description |
|---|---|---|
--strategy=NAME | window | Strategy: window, tfidf, punctuation |
--min-size=INT | 100 | Minimum segment characters |
--max-size=INT | 2000 | Maximum segment characters |
--target-size=INT | 500 | Target segment characters |
--threshold=FLOAT | 0.42 | Divergence threshold |
--window-size=INT | 3 | Window size |
--adaptive | true | Adaptive threshold mode |
--hybrid | false | NCD+TF-IDF hybrid mode |
--ncd-weight=FLOAT | 0.5 | NCD weight in hybrid mode |
--tfidf-weight=FLOAT | 0.5 | TF-IDF weight in hybrid mode |
--prefix=NAME | segment | Output file prefix |
Strategies
| Strategy | Description |
|---|---|
window (default) | Sliding window divergence detection |
tfidf | TF-IDF based topic change detection |
punctuation | Punctuation/sentence boundary based |
Workflow
1. Run indexion segment <input-file> <output-dir> to split text with defaults 2. Adjust --threshold and --target-size to tune segmentation granularity 3. Use --hybrid mode for better accuracy on mixed-content documents
Related skills
Setup Matt Pocock SkillsScaffold the per-repo configuration that Matt Pocock’s engineering agent skills rely on so they understand the issue tracker, triage labels, and domain documentation la495k196k
Lark AppsConnect Claude, Cursor or custom agents directly to Lark (Feishu) for messaging, document automation, approval workflows and enterprise data access.402k
CavemanSlash token usage by roughly 75% while keeping every technical detail intact when working with Claude Code, Cursor or similar agents.391k94.7k
Lark Skill MakerQuickly turn any Lark/Feishu OpenAPI call or multi-step workflow into a reusable agent skill with its own SKILL.md.386k16k
Running Claude Code Via Litellm CopilotRun Claude Code at a fraction of the cost by routing requests through LiteLLM to the GitHub Copilot Chat API.270k72
Codex PetGenerate a complete Codex Pet spritesheet and metadata from one reference image without needing an OpenAI key or Codex Pro.246k10How it compares
Pick indexion-segment over generic fixed-token splitters when chunk boundaries should follow document semantics rather than arbitrary token counts.
FAQ
What does indexion-segment do?
It guides indexion segment CLI usage to split text using window, TF-IDF, punctuation, or hybrid strategies.
When should I use indexion-segment?
When preparing documents for RAG, embeddings, or sub-document similarity at configurable chunk sizes.
Is indexion-segment safe to install?
Review the Security Audits panel on this listing before installing in production.