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How to spot same-day bulk submissions before trusting them with Awesome Jev

Check commit history and shared scaffold files to see if a bulk-submitted repo is proven.

Who it is forA maintainer or curator who sees several repositories from one author added at the same time.

The problemBulk repos can meet every inclusion rule while still being unproven, and volume is not evidence of quality.

The outcomeA clear yes or no on whether a bulk-submitted repository shows real development history and original code.

What you need first

  • A web browser or git
  • A GitHub account if you plan to open an issue or pull request

Steps

  1. Open the repository's commit history and note the number of commits and the dates they were made.
  2. Look in the root folder for the shared scaffold files named in the README: AGENTS.md, CLAUDE.md, STATE.md, and CHANGELOG.md.
  3. Compare the count of prose files to the count of code files.
  4. Check whether the same scaffold appears in other repositories from the same author.
  5. Label the repository as a lead rather than a validated tool if the signals point to a shared template.

Prompt for your agent

Using the Curation is not endorsement section of yibie/awesome-jev as the reference, inspect <repo URL> for commit count, commit dates, the presence of AGENTS.md, CLAUDE.md, STATE.md, and CHANGELOG.md, and the ratio of code to prose files. Expected output: a short verdict of proven, unproven, or unclear with the evidence listed. Verify the verdict against the commit history shown on the repository page.

Caveat. The README describes these signals as a warning, not a rule, so a bulk-submitted repository may still be legitimate.

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Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page