VERBA / PUBLIC PROBLEM LEDGER
Needs surfaced from real conversations, so curious builders can find the next useful thing to make—with the context still attached.
Every post stays connected to its discussion.
474Requests · pain points · open questions
Open ledgerLIVE COMMUNITY SIGNALS
Search the original posts and the conversations around them. The source content remains in its original language.
I started with ChatGPT, then moved to Claude. Though I like Claude, I always hit the basic tier limit despite using it only for less than an hour. Their usage/length limits don't make sense to me at all! I just downloaded Osaurus to give…
From the discussion“Osaurus is awesome!”
EVERY POST CLASSIFIED
Different conversations reveal different kinds of opportunity. Start with the signal that fits how you build.
People actively looking for an app, alternative, or recommendation.
Repeated friction, missing workflows, and things people want fixed.
Questions that expose undecided needs and room for better answers.
Products already in the wild—and the feedback gathering around them.
CONTEXT BEFORE CODE
Verba keeps the problem and its conversation together. You can judge the signal before deciding what, if anything, should be built.
Search direct requests, recurring friction, and questions from real conversations.
Browse needsOpen a demand brief and read the original post alongside every collected comment.
Keep the nuanceCompare discussion depth and source evidence before committing your time to a solution.
Build with evidence6 QUESTIONS
What this first Verba ledger contains, how it was cleaned, and what the numbers mean.
This first dataset is a snapshot of public posts and comments from r/MacApps. Every brief links back to its original Reddit source.
No. Interface text is fully available in English and Simplified Chinese, while community content stays in its original language to preserve meaning.
The cleaner uses Reddit post IDs to group every collected comment under its post. Known reply relationships are preserved; missing thread metadata remains marked unknown.
The scraper exported richer metrics for only part of the dataset. Verba keeps absent values as unknown instead of presenting them as zero.
Not always. The dataset often contains only a sample of a larger thread. Detail pages show collected and reported counts separately whenever both exist.
Yes. The mock endpoints expose searchable, paginated posts and individual post records in the normalized post-to-comments shape.