Readable by humans. Structured for agents.
AI Web Feeds turns a raw ecosystem of feeds, topics, and documentation into a browsable knowledge surface with machine-friendly outputs, clearer navigation, and operational visibility built in.
Curated feeds
Human-reviewed catalog
A cleaner layer over raw RSS, Atom, and JSON feed discovery for AI-heavy workflows.
Machine-friendly outputs
Docs, feeds, and LLM formats
Move from browsing to ingestion quickly with endpoints that fit both humans and agents.
Operational visibility
Analytics and explorer surfaces
Understand topic coverage, feed health, and relationships instead of guessing what the catalog contains.
A better front door into the repository’s feed intelligence.
The main product surfaces are now framed as clear entry points rather than a single undifferentiated card wall. Each one answers a different question: how to use the system, what it contains, how it is performing, and how to export it.
Documentation
Browse guides, API reference, and implementation notes in a format that reads cleanly for both maintainers and agents.
Open surfaceExplorer
Inspect topics and feeds as a searchable table or graph so relationships and gaps become legible fast.
Open surfaceAnalytics
Track health, validation velocity, and trending topics through a calmer dashboard tuned for signal over clutter.
Open surfaceSearch
Find relevant sources quickly with full-text and semantic discovery surfaces built around the catalog.
Open surfaceFeed catalog
Browse the source registry, validation posture, and structured metadata without diving into raw files.
Open surfaceDownloads
Export the catalog in portable formats for feed readers, downstream processing, or local experimentation.
Open surfaceLLM formats
Serve long-form repository knowledge in formats that are easier to consume inside AI workflows and tools.
Open surfaceOpen source and portable
Use the catalog in the browser, through feed formats, or directly from GitHub.
The site remains the human-facing layer, but the same repository still supports downstream automation, feed reader exports, and machine-friendly long-form docs.
Open source project by Wyatt Walsh · View on GitHub