# Cluster Documents > Automated content similarity and grouping analysis. Groups related documents by topic, purpose, or content similarity. Use when this capability is needed. - Skill: `tomevault-io/cluster-documents` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/cluster-documents` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/cluster-documents/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/cluster-documents --- # Document Clustering Skill Analyze a repository of documents to group them based on content similarity, topic, or purpose. This skill helps organize large collections, identify redundancies, and discover relationships. ## Inputs - `PATH` - The repository to analyze (e.g., "/repository") - `SIMILARITY_THRESHOLD` - (Optional) Float (0.0-1.0), threshold for grouping (default: 0.8) - `VISUALIZATION` - (Optional) Boolean, whether to generate a visual representation (default: false) ## Workflow ### Step 1: Text Processing Ingest documents from `PATH`. - Normalize text (remove stop words, stemming/lemmatization). - Generate embeddings or TF-IDF vectors for each document. ### Step 2: Clustering Analysis Apply clustering algorithms (e.g., K-Means, DBSCAN) to the document vectors. - Group documents that meet the `SIMILARITY_THRESHOLD`. - Identify outliers or unique documents. ### Step 3: Cluster Labeling Analyze the centroid or representative terms of each cluster to assign a meaningful label (Topic). ### Step 4: Output Generation Generate the clustering report. - If `VISUALIZATION` is true, create a scatter plot or dendrogram data. ## Required Outputs A `CLUSTERING_REPORT` object containing: - **Cluster List**: ID, Label, and List of Documents in each cluster. - **Redundancy Report**: Sets of highly similar documents (potential duplicates). - **Visualization Data**: (If requested) Coordinates for plotting. ## Quick Reference - **Purpose**: Organize unstructured content and find duplicates. - **Techniques**: Text Mining, NLP, Vector Space Models. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/dandye) — claim your Tome and manage your conversions.