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Deadfolio.

An autopsy for the GitHub projects you left behind.

  • Next.js
  • TypeScript
  • Gemini
  • Vercel AI SDK
  • Zod
  • Vercel Blob
  • Tailwind CSS
Deadfolio home page in Brazilian Portuguese: headline saying your GitHub is full of projects left behind and Deadfolio finds them, with buttons to analyze a GitHub profile or paste a repository.

Overview

Paste a public GitHub username and Deadfolio scores every public repository for signs of abandonment. On the ones worth a look, it runs an AI autopsy built from the repository's own evidence. Nobody is asked about their stack, project age or activity, because the repository already knows. The one question a person answers is why they actually stopped. The app is available in English and Brazilian Portuguese.

What it does

  • Scan: a Dead Score from 0 to 100 for each public repository, from metadata only. No AI runs at this step.
  • Autopsy: one Gemini generation per repository, validated against a strict schema and always ending with a “What We Cannot Know” section.
  • Confirm: the creator says whether the inferred cause of death is right and can correct it in one sentence.
  • Graveyard: published records, labeled UNVERIFIED because repository ownership is not verified.

How it’s built

  • The Dead Score is deterministic and configurable: an inactivity ramp, archive status, and short bursts followed by silence. Forks, templates and experiments are kept apart, and the interface calls the score a heuristic, never a probability.
  • The prompt treats repository text as untrusted data and keeps evidence, inference and unknowns separate. The model may not invent users, revenue or the real reason development stopped.
  • Evidence collection ranks files deterministically, never fetches secrets, lockfiles or build output, and scrubs key-like strings before anything reaches the model.
  • Reports are cached by repository and default-branch commit, so a repeat visit makes no AI call. A new commit triggers an offer to run a fresh autopsy.
  • Abuse limits include a per-IP daily quota stored as a salted hash, one concurrent autopsy per IP, a global hourly guard, and a quota refund when the AI provider is at capacity.
  • It is one Next.js app with no database: a key/value layer writes to the filesystem locally and to a private Vercel Blob store in production.

Deliberate limits

  • No accounts, payments, notifications or moderation, on purpose.
  • Only public repositories are analyzed.
  • Ownership is not verified, so every published record is labeled UNVERIFIED.