Data documentation in psychology lags behind not only many other disciplines, but also basic standards of usefulness. Psychological scientists often prefer to invest the time and effort necessary to document existing data well into other duties such as writing and collecting more data. Codebooks therefore tend to be unstandardised and stored in proprietary formats, and are rarely properly indexed in search engines. This means that rich datasets are sometimes used only once—by their creators—and left to disappear into oblivion; even if they can find it, researchers are unlikely to publish analyses based on existing datasets if they cannot be confident they understand them well enough. My codebook package makes it easier to generate rich metadata in human- and machine-readable codebooks. By using metadata from existing sources and by automating some tedious tasks such as documenting psychological scales and reliabilities, summarising descriptives, and identifying missingness patterns, I aim to encourage researchers to use the package for their own or their team's benefit. The codebook R package and web app make it possible to generate rich codebooks in a few minutes and just three clicks. Over time, this could lead to psychological data becoming findable, accessible, interoperable, and reusable, and to reduced research waste, thereby benefiting the scientific community as a whole.