What problem does it solve?
It solves the problem of turning incoming external content (URLs, files, or pasted text) into a persistently organized local knowledge base without missing links, duplicates, or broken references.
Core Features & Use Cases
- URL/file ingestion workflow: Fetch content (with URL dedupe and stateful resume) and convert it into corpus-ready wiki entries with proper filing rules.
- Entity/concept page building with timeline: Identify main subjects, gate for notability, then create new pages or append a
## Timeline entry with 強化 / 修正 / 新增分歧 annotations.
- Backlink and integrity safeguards: Pre-check dead links (
ingest check), align aliases to avoid duplicates, record source hashes (raw_sha256), and finish with a single multi-step closure (ingest record), followed by sync to refresh indexes and vectors.
Quick Start
Trigger ingest by telling your AI: ingest https://example.com/some-article and store it into my knowledge base with backlinks and timeline updates.