RepoLogbook
Methodology ยท version 1

Every number should be explainable.

Definitions, freshness, transformations, and known limits for repository analytics. No invented precision and no visitor-level claims.

Bundled methodology

Freshness is explicit

Collection runs on a daily schedule. Each report shows when its immutable snapshot was generated.

Gaps stay visible

A missing day means no trustworthy observation was stored. Missing values are not silently converted into zero activity.

Aggregate, not identity

Reports contain repository-level aggregates only. They cannot identify individual visitors, cloners, or README viewers.

Metric dictionary

What each signal means

Metrics retain the vocabulary of their upstream source. Derived values are labeled as derived.

views

Views

Repository page views reported by GitHub for each UTC day.

uniqueViews

Unique views

GitHub's daily estimate of distinct repository viewers.

clones

Clones

Repository clone events reported by GitHub for each UTC day.

uniqueClones

Unique clones

GitHub's daily estimate of distinct cloners.

stars

Stars

Net star gains derived from cumulative repository snapshots and historical stargazer events.

forks

Forks

Net fork gains derived from cumulative repository snapshots.

genuineSubscribers

Genuine subscribers

The repository watcher count from GitHub, excluding stars and social followers.

releaseDownloads

Release downloads

Downloads reported for release assets during the selected interval.

packageDownloads

Package downloads

Downloads reported by the supported package registry during the selected interval.

Chart transformations

Same facts, different lenses

01

interval

Shows the value recorded in each reporting interval.

02

cumulative

Adds each interval to the running total.

03

normalized

Rebases each selected repository to 100 at the beginning of the window for relative comparison.

04

rolling

Shows a trailing average across the selected number of days.

Interpretation guardrails

Unique counts are upstream estimates and should not be summed into a person-level total. A README view cannot be identified. Correlation between a release and a traffic change is context, not proof of conversion. Anomaly flags are deterministic observations, not forecasts.