Want to grow your open-source project? Study the ones that did. Steal their playbook.
See how projects went from zero to thousands of stars — the launches, Show HN posts, releases, communities and tactics that happened along the way. Pigtail reconstructs the public evidence so you can see what they tried, when they tried it, and what happened next.
Why did this repo keep moving?
Example reports generated by Pigtail.
Each card is a report Pigtail produced from public sources. Open one to see the full output: timeline, growth episodes, tactics, gaps and sources.
PocketBase
A one-developer backend whose stars grew in bursts, mostly from posts by other people.
Hatchet
An open-source task queue that launched repeatedly on Hacker News — Show HN, Launch HN, then v1.
Plausible Analytics
Privacy-first analytics that grew through opinionated blog posts reaching Hacker News, alongside a bootstrapped paid cloud.
You shipped it. Now how do you get anyone to care?
You can read another generic thread telling you to post on Hacker News, launch on Product Hunt and “build in public.” Or you can inspect what real projects actually did — at the stage they did it — and what happened afterward.
Repo in. Growth trail out.
Pigtail does the source hunting and reconstruction, then gives you both a human-readable forensic and structured research data.
Give it a repo or product.
Start from a public GitHub repository or a product website.
Pigtail gathers the evidence.
Repository history, releases, launch posts, Hacker News, Product Hunt, founder material, interviews and other public evidence.
Inspect what happened.
Growth timeline, launch history, metrics, tactics, growth engines, gaps and sources — plus the Research Bundle behind it.
Interesting without pretending correlation is causation.
The point is not to manufacture a clean founder story. It is to reconstruct what public evidence can actually support.
Every material claim points back.
Claims retain the source, date and supporting material so you can inspect the trail yourself.
Timing is not cause.
An event near a star spike is shown as an observed association unless stronger attribution evidence exists.
“We don’t know” is allowed.
If no high-confidence public event explains a growth episode, Pigtail says so instead of inventing a narrative.
See what Pigtail finds in your growth trail.
Free and open source. Runs locally. No subscription: you only pay your own Anthropic API usage, usually a few dollars or less per report. Reddit search is optional: add your own free Reddit API keys to include Reddit posts. Your output is a portable HTML forensic plus a structured Research Bundle.
$ pigtail https://github.com/owner/repository ✓ Resolve target ✓ Repository history ✓ Discover sources ✓ Fetch evidence ✓ Extract claims ✓ Reconstruct timeline ✓ Analyze growth ✓ Validate evidence and gaps ✓ Write Research Bundle ✓ Render report → report.html → research-bundle.json
Which repo should Pigtail investigate next?
Found a project with a fascinating growth curve? Request a forensic and help build a public library of how open source actually grows.
Request a repo forensic →