How it works
Million Keywords is built around a predictable audit loop. If you work with release files, documentation, localization exports, App Store metadata, or other text-heavy folders, this is the fastest way to move from raw files to CSV-ready evidence.
Start by selecting the folder you want to scan. The app walks the directory recursively, so nested text files are included automatically. This makes it useful for release bundles, support-center exports, content archives, and localization folders.
Load a plain-text file with one keyword per line. Inside the app, you can reload the source, deduplicate repeated entries, sort alphabetically, and save a normalized version before scanning.
Adjust the file extensions that count as text input and decide whether matching should be case sensitive. This matters when your corpus mixes markdown, text exports, raw localization files, or machine-generated output.
The scan view shows progress, document counts, matched documents, failures, and performance hints. If you are on the free tier and exceed the included limits, the app will stop you before the full scan begins.
Review matched files, search paths and filenames, switch between file and keyword result modes, and sort by occurrences, path, size, or document count. This lets you answer both “where does this term appear?” and “which terms are really dominant?”
Export file summaries, keyword summaries, and match details to CSV so the scan can feed spreadsheet review, QA signoff, operations reporting, or release documentation.
Good scanning habits
A clean source file makes deduplication and result review much easier.
Scanning only relevant text formats reduces noise and speeds up review.
Sort by occurrences when chasing density, or by path when auditing structure.
CSV outputs give other stakeholders a durable artifact without sharing the whole folder.
