A shell-native cd-compatible directory jumper using power-law frecency
I have used this tool privately since 2011 to manage directory jumping. While it is conceptually similar to tools like z or zoxide, the underlying ranking model is different. It uses a power-law convolution with the time series of cd actions to calculate a history-aware "frecency" metric instead of the standard heuristic counters and multipliers. This approach moves away from point-estimates for recency. Most tools look only at the timestamp of the last visit, which can allow a "one-off" burst of activity to clobber long-term habits. By convolving a configurable history window (typically the…
In plain words
This shell-native directory jumper helps users navigate frequently-used folders by learning from their cd history. It ranks directories using a power-law frecency model that considers patterns across hundreds of past actions rather than just the most recent visit, preventing occasional bursts of activity from disrupting long-term navigation habits. Query responses complete in 20-30 milliseconds, remaining fast enough for seamless shell integration. The tool has been privately maintained since 2011 and is designed for developers and power users who frequently switch between multiple project directories.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I have used this tool privately since 2011 to manage directory jumping. While it is conceptually similar to tools like z or zoxide, the underlying ranking model is different. It uses a power-law convolution with the time series of cd actions to calculate a history-aware "frecency" metric instead of the standard heuristic counters and multipliers. This approach moves away from point-estimates for recency. Most tools look only at the timestamp of the last visit, which can allow a "one-off" burst of activity to clobber long-term habits. By convolving a configurable history window (typically the last 1,000+ events), the score balances consistent habits against recent flukes. On performance: Despite the O(N) complexity of calculating decay for 1,000+ events, query time is ~20-30ms (Real Time) in ksh/bash, which is well below the threshold of perceived lag. I intentionally chose a Logical Path (pwd -L) model. Preserving symlink names ensures that the "Name" remains the primary searchable key. Resolving to physical paths often strips away the very keyword the user intends to use for searching.
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