Cortex v1.2: LLM Enrichment, Q&A with Citations, Conflict Resolution

Cortex is a local memory layer built for OpenClaw agents, designed to prevent context loss during compaction. The project recently reached 10 GitHub stars and has progressed from v1.0 to v1.2 within a week, with the developer using it daily with two agents.

New features in v1.2

LLM-augmented enrichment enabled by default: When importing files, Cortex now uses Grok to enrich extracted facts with context like relationships, classifications, and provenance. The entire enrichment pipeline costs less than a dollar per month. You can disable it with --no-enrich for pure offline mode.
Question answering with citations: The new cortex answer command lets you ask questions and receive synthesized answers with citations back to original memories. It includes built-in prompt injection defense to prevent imported content from hijacking responses.
Deduplication and conflict resolution: cortex cleanup --dedup-facts finds near-duplicate facts and supersedes older ones. cortex conflicts --resolve llm detects contradictions and auto-resolves them using an LLM, maintaining an audit trail of changes and reasons.
Unified configuration: cortex config doctor shows exactly what's configured, where each value comes from (default, environment variable, flag, or config file), and what's missing.
Intent-based search pre-filtering: Search now classifies query intent (lookup, temporal, relational, etc.) and pre-filters results by fact type before scoring. For example, "when did I deploy v2?" prioritizes temporal facts, while "who works on XXX?" prioritizes relationship facts.

Upcoming development

The developer is currently dogfooding v1.3, which adds scoped views for multi-agent setups and an Obsidian connector that syncs vaults into Cortex as a searchable knowledge layer. The Obsidian connector is available in the repository but hasn't been audited yet.