Devthropology – Better Insights for GitHub Repos
Devthropology is a passion project built on top of GitHub pull data. The name is a play on developer anthropology. Pull request data can be cut a lot of ways. The functionality has been built out of curiosity as I want to see different insights into codebases that I work on. Some of the data is typical and other parts I haven't seen elsewhere. I think of this as an improved GitHub Insights page, with faster performance, more detail, and a focus on how work moves through a codebase. The main entity is a contributor, which has two sides: authoring PRs and reviewing/giving feedback to…
In plain words
Devthropology analyzes GitHub pull request data to provide insights into how work moves through codebases. Built as an alternative to GitHub's native insights page, it offers faster performance and more granular detail on contributor activity, code health, collaboration patterns, and velocity trends. The tool examines both pull request authorship and code review involvement, displaying repository-wide statistics, user interactions, and contribution trends to help developers understand their codebase dynamics.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Devthropology is a passion project built on top of GitHub pull data. The name is a play on developer anthropology. Pull request data can be cut a lot of ways. The functionality has been built out of curiosity as I want to see different insights into codebases that I work on. Some of the data is typical and other parts I haven't seen elsewhere. I think of this as an improved GitHub Insights page, with faster performance, more detail, and a focus on how work moves through a codebase. The main entity is a contributor, which has two sides: authoring PRs and reviewing/giving feedback to others. From there, you can see repository wide stats, user interactions, contribution trends, file health, and collaboration patterns. Some insights are useful for understanding velocity and code health in the AI era. Details for each page: - Homepage: A high level summary of the repository. Showing age, file types, active contributors, new and churned users. I track the author age at merge, so you can see the tenure of people shipping changes over time. - File explorer: One of my favorite parts. I build a graph of files, tracking renames and moves, to build a complete history. Rolling up, every file and folder is assigned an outlook such as active, developed, stale, touched by people who are likely gone. You can easily see contributor timelines, recent changes, and for some files, their rename/move history and related files that often change together (useful for a coding agent). - Trends: The densest page, showcasing the velocity of contributions and trying to understand if AI is helping ship more. Charts are cut by year for comparisons, tracking PR size, output, rounds of review, and approval latency by different percentiles. PRs are further cut into bucketed sizes to help drill in deeper. Helps to show that smaller PRs are likely still faster to ship while very large PRs (product of AI?) are slowing down. - Relationships: A graph of interactions between contributors, weighted by PR activity, with a simple algorithm. Communities are grouped with links showing one way vs bidirectional. You can adjust time or raise the score to filter out noise. Clicking on contributors shows the scores of interactions and if they mostly give or receive feedback. - Contributors: Search all contributors, showing a few lifetime metrics. Clicking in shows an overview of their profile with some high level details. A few author/reviewer specific stats are shown across four time frames with their rank, each row is clickable. Below that is recent author/reviewer PR activity, including rounds, comments, and review timing. - Author/Reviewer reports: A handful of metrics showing performance of a contributor from both sides of a PR, one as an author and one as a reviewer. Cells are color coded and bucketed into tiers to easily see where someone sits in the repository. Can be filtered by user, team, or time. Couple of key terms and limitations: - Contributor is any account that has authored or commented on a PR that’s been merged. This can include bots - Round of review / “round” occurs when a nonauthor leaves comments and the author pushes more commits; tries to simulate a back and forth. - “Effective" approval is the approval that actually matters for merging, i.e. the first approval after the last round of review. Example: A opens a PR, B approves, C then requests changes and A pushes more commits, C approves, C's approval is the effective one (B's is stale). - Trends/Reports can be filtered by team but unfortunately without a private API key, I cannot sync teams. For a few repos I have created a few small teams Please take a look, there's a lot of buttons, dropdowns, and clickable links. The demo repos were selected because they are private companies building in the open, with patterns similar to private repos: smaller contributor sets and more activity per contributor. Appreciate any feedback below or at [email protected]
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