semantica-agi/semantica
Graph-native context, provenance, ontology, and accountable-AI layer for agents — the #1 repo out of the Sept 9 run.
Activity
Pushed Sep 9; temporal graph, vector-store, CI fixes today.
What to Study
Temporal graphs, provenance, ontology boundaries, and accountable reasoning.
Why It Matters
Graph-native context, provenance, ontology, and accountable AI maps directly to AutoNateAI's graph-first systems thinking.
Action
Run locally; map the data model; benchmark against a simpler vector-RAG baseline.
Notes
- Candidate for the Context Graph vs. Context Database benchmark
- Watching for architecture writeups and maintainer activity
AutoNateAI Experiments Using This
ProposedProcedural Graph Runtime
Can a validation-gated, self-evolving execution graph improve long-horizon agent workflows without increasing unsafe tool use?
hub Inspectable Agent Systems
ProposedIndependent Test Agent
Does separating an independent Test agent from a Repair agent reduce false-confidence patches without hurting resolution rate?
hub Inspectable Agent Systems
ProposedRevocable Memory Graph
Can a graph-based retriever enforce memory revocation structurally while still preserving useful personalized context?
hub Inspectable Agent Systems
ProposedSafety Judge Stress Lab
Which content-invariant wrapper transformations produce the highest disagreement across automated safety judges, and can simple ensembles resist them?
hub Inspectable Agent Systems
ProposedContext Graph vs. Context Database
Does explicit graph structure improve retrieval traceability and multi-hop reasoning over a context-database approach, at the same token cost?
hub Inspectable Agent Systems