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@nanomind/runtime-core
Advanced tools
NanoMind RuntimeTwin: behavioral twin (LSTM) for ARP anomaly detection. Canonical home of the LSTM scorer referenced in NANOMIND_V3_AUDIT.md Section 9 item 1.
RuntimeTwin: behavioral twin (LSTM) for ARP anomaly detection.
This package is the canonical home of the LSTM behavioral scorer that sits between L0 rule-based classification and L2 LLM-assisted assessment in the three-tier ARP intelligence stack. Each ARP event flows through the twin on a non-blocking path. The twin computes an anomaly score against a warm-up baseline, contributes to federated learning via differential-private gradient submissions, and hands a BehavioralRiskScore back to the coordinator.
RuntimeTwin class when the package is published.hackmyagent/src/arp/intelligence/runtime-twin.ts temporarily mirrors this source. Any change to scoring logic must be mirrored in both files until the publication cut-over (tracked as PR 1b in todo/NANOMIND_V3_AUDIT.md Section 8).Section 9 item 1 of the v3 audit found two parallel behavioral-twin implementations: a statistical twin in packages/nanomind-runtime/ and an LSTM twin in hackmyagent/src/arp/intelligence/nanomind-l1.ts. Abdel approved path (a) on 2026-04-11: retire the statistical twin, relocate the LSTM to this package. This package is the result.
This twin produces 9-dimensional gradients that feed /api/v1/telemetry/behavioral-gradient. The current submission path uses the v1 wire format; NANOMIND_FL_DESIGN.md Section 3 deliberately supersedes it with the v2 format (signed, round-aware, client-identified). The v2 adoption is tracked separately; this package does not implement v2 yet.
hackmyagent/src/arp/.guard-anomaly, still in hackmyagent/src/arp/intelligence/.FAQs
NanoMind RuntimeTwin: behavioral twin (LSTM) for ARP anomaly detection. Canonical home of the LSTM scorer referenced in NANOMIND_V3_AUDIT.md Section 9 item 1.
The npm package @nanomind/runtime-core receives a total of 2 weekly downloads. As such, @nanomind/runtime-core popularity was classified as not popular.
We found that @nanomind/runtime-core demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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