Analysis updated 2026-07-08 · repo last pushed 2026-07-07
Add a contributor breakdown chart to your open-source project's README.
Visualize how work is distributed across your team members.
Highlight top contributors with avatars while bundling minor contributors into a secondary section.
| haruko386/repositoryblame | 0xhassaan/nn-from-scratch | a-little-hoof/dsr | |
|---|---|---|---|
| Stars | — | 0 | 0 |
| Language | Python | Python | Python |
| Last pushed | 2026-07-07 | — | — |
| Maintenance | Active | — | — |
| Setup difficulty | easy | moderate | hard |
| Complexity | 2/5 | 4/5 | 5/5 |
| Audience | developer | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires adding a configuration file and GitHub Actions workflow to your repository, plus write permissions to push the generated SVG to a branch.
RepositoryBlame generates a visual chart showing what percentage of your codebase each contributor wrote. You get an SVG image that you can drop right into your project's README, so visitors instantly see who built what. The tool runs inside GitHub Actions, so you just add a configuration file to your repository and it handles the rest. It scans your source files using git blame, which figures out who last touched each line of code. Then it cross-references each change with GitHub's commit data to resolve real usernames and avatars. The final chart is pushed to a separate branch in your repo, and you link to it like any other image. This is useful for open-source maintainers who want to highlight their community, or for team leads who want a quick visual of how work is distributed. For example, a project with dozens of contributors can show the top ten as named entries with avatars, while everyone below a threshold (say, 0.8%) gets bundled into a smaller secondary area. You can configure how many contributors appear in each section and filter out directories like node_modules or vendor so the stats reflect meaningful code, not dependencies. One thing worth noting is that the whole approach relies on git blame, so it credits whoever made the most recent change to each line, not necessarily the original author. If someone reformats a file, they might show up as the contributor for those lines. The README doesn't discuss this tradeoff, but it's inherent to how the underlying tool works. The setup also requires write permissions to push the generated image to a branch, which is standard for this kind of automation.
A GitHub Actions tool that scans your codebase with git blame and generates an SVG chart showing what percentage of code each contributor wrote, so you can display contributor breakdown directly in your README.
Mainly Python. The stack also includes Python, GitHub Actions, Git.
Active — commit in last 30 days (last push 2026-07-07).
No license information was provided in the repository explanation, so the licensing terms are unknown.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.