Build and query focused knowledge graph subgraphs locally on resource-limited edge devices for low-latency, offline-aware reasoning and incremental updates.

This skill is a high-level design/instruction document (no code, no installs, no credentials requested), and appears internally consistent with its stated goal. Still consider: (1) provenance — source and homepage are missing, so if you later install an implementation based on these instructions, audit that code and packages before running on devices; (2) testing — try implementations in a sandbox or isolated edge device before deploying to production; (3) least privilege — never supply cloud credentials or device admin credentials unless a concrete implementation legitimately requires them and you’ve reviewed that code. If you want a runnable implementation, ask the author for source (repo, releases) and a clear install plan so you can review packages and update mechanics.

Type: OpenClaw Skill Name: edge-knowledge-graph Version: 1.0.0 The skill bundle consists of metadata and conceptual documentation (SKILL.md) regarding the implementation of knowledge graphs on edge devices. It contains no executable code, scripts, or instructions that attempt to exfiltrate data, gain unauthorized access, or perform malicious actions. The content is purely educational and theoretical in nature.