Documentation

Official Indexly documentation hub for installation, environment setup, search, structured-data analysis, AutoDoctor artifact workflows, backup, and developer setup.
Categories:
Tags:

Welcome to the Indexly documentation hub.

Indexly is a local-first CLI for indexing, searching, analyzing, and organizing files without sending your data to external services.

Documentation Paths

This documentation works best when you enter through the path that matches your goal:

  • Everyday CLI path: install, index, search, tag, organize, and back up local content
  • Structured data path: prepare filenames, analyze CSV, JSON, NDJSON, SQLite, and AutoDoctor artifacts
  • Developer path: understand architecture, command wiring, and optional dependency boundaries
  • Contributor environment path: prepare a maintained Windows or Linux workstation for Indexly development

What Is New

Start Here

Quick Workflow 

flowchart LR
    A["Install (pip or Homebrew)"] --> B["Index Local Files"]
    B --> C["Search / Regex"]
    C --> D["Tag, Organize, and List"]
    D --> E["Analyze Data (CSV/JSON/DB)"]
    E --> F["Compare, Backup, Restore"]
    F --> G["Observe, Doctor, and Maintain DB"]

Documentation Map

Goal Recommended Page
Install and verify on Windows, macOS, Linux Install Indexly
Prepare the maintained contributor workstation Windows Development Environment Setup, Linux Development Environment Setup
Learn command workflows end-to-end Usage Guide
Standardize filenames before analysis or organization Rename File
Remove stale search results without deleting files Clear Search Results Safely
Diagnose search, cache, analysis DB, and integrity issues Indexly Doctor
Get short answers for setup, paths, file support, and troubleshooting FAQ
Choose the right analysis command and pipeline Data Analysis Overview
Analyze JSON, NDJSON, search cache JSON, or Socrata-style JSON Analyze JSON And NDJSON Files
Analyze CSV files with summaries, charts, and exports Analyze CSV
Clean CSV files before analysis Clean CSV Data
Analyze AutoDoctor report JSON, telemetry JSON, or SQLite output Analyze AutoDoctor Artifacts
Improve indexing quality and ignore rules Ignore Rules & Index Hygiene
Organize folders and inspect logs Organizer, Lister
Run semantic observers and audit stored snapshots Observers
Analyze generic SQLite datasets deeply Analyze SQLite Databases
Run statistical inference for CSV datasets CSV Inference
Compare files and folders safely File & Folder Comparison
Maintain health and schema consistency Indexly Doctor, DB Migration Utility
Extend or contribute to the project Developer Guide

Cross-Project Notes

Indexly now includes an AutoDoctor documentation subtree under this same Hugo site. That gives you two useful perspectives:

  • Use Indexly docs when your goal is: “How do I analyze this artifact with Indexly?”
  • Use AutoDoctor docs when your goal is: “What does this artifact mean in the AutoDoctor system?”

Good companion pages:

Notes For Developers

If you are contributing code, start with:

  1. Developer Guide
  2. Contributing Guide
  3. indexly show-help --details for parser-level command scope

License

Indexly is licensed under the MIT License.

AutoDoctor Documentation

Official AutoDoctor documentation for users, technical operators, and developers. Covers installation, configuration, diagnostics, remediation, API, dashboard, and troubleshooting.

Why This Matters

Understand why Indexly’s semantic-aware indexing makes search reliable, fast, and human-friendly.

Install Indexly – Setup, Configuration & First Run

Install Indexly on Windows, macOS, and Linux with clear steps for pip and Homebrew. Includes verification, optional feature packs, and troubleshooting.

Windows Development Environment Setup

Production-ready Windows setup guide for Indexly contributors. Covers PowerShell 7, Windows Terminal, Scoop, winget, dotfiles-windows bootstrap, project-indexly setup.ps1, verification, and troubleshooting.

Linux Development Environment Setup

Production-ready Linux contributor environment guide for Indexly. Covers the standalone dotfiles-linux bootstrap flow, full dotfiles repo mode, local profile sync with update-lp, Homebrew/Linuxbrew tooling, Project-Indexly docs commands, verification, rollback, and known Ubuntu support notes.

Analyze JSON And NDJSON Files

Use Indexly to analyze JSON, NDJSON, compressed JSON, Socrata-style JSON, and Indexly search-cache JSON with safe sampling and strict record handling.

Indexly Usage Guide

Practical Indexly usage guide for Windows, macOS, and Linux. Covers indexing, search, regex, tagging, analysis, organizing, backup/restore, and common troubleshooting.

Configuration and Runtime Files

Configure Indexly runtime paths, search profiles, search cache behavior, analysis persistence, indexing log artifacts, tags, OCR choices, and maintenance commands.

Ignore Rules & Index Hygiene

Index Files and Folders with Indexly

Learn how to index files and folders with Indexly using simple CLI commands. Filter by file type, enable advanced extraction, and keep your index up to date automatically.

Clear Search Results Safely

Use the Indexly clear-search command to safely remove indexed FTS5 search entries by path, tag, or full index with dry-run previews, confirmations, cache handling, and audit logs.

Semantic Indexing in Indexly – Overview

Understand why semantic indexing exists in Indexly, how it fixes real-world search relevance issues, and how rule-based semantic filtering improves results in large local databases.

Semantic Indexing & Vocabulary Quality

Indexly Tagging System

Learn how to use Indexly’s powerful file tagging system to categorize, organize, and search files effortlessly. Supports bulk tagging, recursive folder tagging, and instant tag lookups.

Virtual Tag Detection

Learn how Indexly detects virtual tags from DOCX tables, email metadata, and conservative regex fallback patterns during indexing, then stores them as searchable file tags.

Renaming Files with Patterns

Standardize filenames in Indexly with rename-file patterns, dry-run previews, optional database path sync, and direct handoff into profile-based organization.

Indexly Organizer – Intelligent File Organization

Automatically organize files by date, name, or extension with full logging, backups, duplicate detection and audit support using Indexly Organizer.

Indexly Organizer – Profile-Based, Auditable File Organization

Safely organize and classify files using intelligent profiles with full logging, hashing, audit trails, dry-run planning, and automation support in Indexly Organizer.

Lister – Analyze Organized Files & Detect Duplicates

Use Indexly Lister to analyze organizer logs, filter files by extension, category, date, and detect duplicates with zero risk.

Indexly Data Analysis & File Pipeline Overview

Understand how Indexly analyzes CSV, JSON, NDJSON, SQLite, Excel, XML, YAML, and Parquet files through its universal loader and specialized pipelines.

Analyze CSV Data

Analyze CSV files with Indexly using delimiter detection, numeric statistics, optional cleaning, terminal charts, static or interactive visualizations, and exports.

CSV Inference

Run statistical inference over persisted or path-based CSV datasets with explicit dataset resolution and merge diagnostics.

Clean CSV Data

Clean CSV files with Indexly using datetime parsing, missing-value filling, derived date features, normalization, outlier removal, and analysis persistence.

Time-Series Visualization in Indexly

How Indexly detects, prepares, resamples, and visualizes time-series data using Plotly and Matplotlib. A complete guide to frequency conversion, rolling windows, dual-axis handling, and statistical considerations.

Database Analysis – Analyze SQLite Databases

Analyze SQLite databases with Indexly to extract table summaries, detect relationships, generate ER diagrams, and export structured insights in JSON, Markdown, or HTML.

Chinook DB Examples – Real-World SQLite Analysis

Explore how Indexly analyzes the Chinook sample database: table summaries, relationships, ER diagrams, and exported Markdown reports from a real-world multi-table SQLite database.

The Story of Chinook – A Narrative SQLite Database Case Study

Explore the Chinook sample database through a narrative lens. Understand tables, relationships, and real-world data structure while seeing how Indexly brings SQLite databases to life.

Analyze AutoDoctor Artifacts

Use Indexly to analyze AutoDoctor report JSON, telemetry JSON, and SQLite artifacts with the dedicated analyze-autodoctor workflow and related generic routes.

Minitab MTW files

Learn how to extract, decode, and analyze Minitab MTW files using Indexly’s extract-mtw feature — including cleaner worksheet CSV output, notes files, and optional diagnostic streams.

Indexly File & Folder Comparison – Context-Aware Diffing

Compare files and folders using Indexly with GitHub-style diffs, similarity scoring, context folding, and JSON output.

Backup & Restore

Incremental, encrypted backups with automatic scheduling and reliable restore chains in Indexly.

Semantic Observers

Semantic observers let Indexly detect meaningful file changes, not just filesystem events.

Indexly Doctor

Use indexly doctor to inspect Indexly health, runtime paths, search database readiness, analysis persistence, cache state, optional dependencies, and safe repair options.

Database Design

Database Update & Migration Utilities

Learn how to safely update, migrate, and manage your Indexly database schema and FTS5 tables without losing data. Includes full CLI examples and explanations of key differences between normal and FTS5 tables.

Indexly Logging System – NDJSON Standard and Legacy .log Support

Understand Indexly’s logging architecture, including the modern NDJSON-based logging system and legacy .log support. Learn how logs are structured, rotated, analyzed, and migrated.

Legacy .log Logging System – Full Documentation

Complete documentation of Indexly’s legacy .log-based logging system. Learn how classic log files are parsed, cleaned, normalized, exported, and migrated to the modern NDJSON logging standard.

Indexly Developer Guide

Learn how to develop Indexly safely and efficiently. Covers project structure, optional dependency design, command wiring, quality checks, and Homebrew-friendly packaging practices.

Why Semantic Filtering Matters

FAQ

Frequently asked questions for installing, using, troubleshooting, and maintaining Indexly across supported platforms.