Feature Surface
The product layer for a crawler pipeline that already thinks in systems.
MindSpider reads best when its features are framed as operational moves: discover early, crawl deeper, keep evidence queryable, and stay honest about what the code is actually doing.
Core Claim
MindSpider is strongest when you need more than trend snapshots but less than a full bespoke intelligence platform. It is opinionated, inspectable, and built around turning public topic motion into reusable structured data.
Signal capture before sentiment depth
MindSpider separates broad discovery from deep crawling, which keeps the expensive platform pass focused on topics that already show momentum.
Keyword queues with operator intent
Topics are not dead-end summaries. They become queues of keywords that can be reviewed, retried, expanded, and assigned to specific crawler passes.
Real browser automation where it matters
The platform layer leans on Playwright so dynamic pages, infinite lists, and auth-gated flows behave more like the surfaces analysts actually inspect.
Schema-first persistence
Tasks, topics, relationships, and platform outputs are modeled as tables, which keeps later querying and report generation tractable.
Reviewable open-source architecture
The most valuable part of the project is that the assumptions are inspectable: how sources are chosen, how crawls fan out, and how storage is organized.
Designed for topic operations, not vanity scraping
The system is organized around answering what people are reacting to, where sentiment clusters, and how discussion evolves after a topic breaks.
Ready to review the current setup path?
The setup page and public repositories show how the project is meant to be evaluated today. That is enough to move from curiosity to source-level inspection.