docs: rvCSI edge RF sensing platform — PRD, ADR-095, DDD domain model

Adds design documentation for rvCSI, a Rust-first / TypeScript-accessible /
hardware-abstracted edge RF sensing runtime that normalizes WiFi CSI from
Nexmon, ESP32, Intel, Atheros, file and replay sources into one validated
CsiFrame schema, runs reusable DSP, emits typed confidence-scored events,
and bridges to RuVector RF memory, an MCP tool server and a TS SDK.

- docs/prd/rvcsi-platform-prd.md — purpose, users, success criteria,
  FR1-FR10, NFRs (safety/perf/reliability/privacy/security/portability),
  system architecture, runtime components, reference layout, data model
- docs/adr/ADR-095-rvcsi-edge-rf-sensing-platform.md — the 15 architectural
  decisions (Rust core, C-at-the-boundary, TS SDK via napi-rs, normalized
  schema, validate-before-FFI, CSI-as-temporal-delta, RuVector as RF memory,
  replayability, detection != decision, local-first, read-first/write-gated
  MCP, mandatory quality scoring, versioned calibration, plugin adapters)
- docs/ddd/rvcsi-domain-model.md — 7 bounded contexts (Capture, Validation,
  Signal, Calibration, Event, Memory, Agent) with aggregates, invariants,
  context map, data model and domain services
- indexed in docs/adr/README.md and docs/ddd/README.md; CHANGELOG entry

Design-only; no code or crates added yet.

https://claude.ai/code/session_01CdYAPvRTjcch6YrYf42n1z
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| [Sensing Server](sensing-server-domain-model.md) | Single-binary Axum server: CSI ingestion, model management, recording, training, visualization | 5 contexts: CSI Ingestion, Model Management, CSI Recording, Training Pipeline, Visualization |
| [WiFi-Mat](wifi-mat-domain-model.md) | Disaster response: survivor detection, START triage, mass casualty assessment | 3 contexts: Detection, Localization, Alerting |
| [CHCI](chci-domain-model.md) | Coherent Human Channel Imaging: sub-millimeter body surface reconstruction | 3 contexts: Sounding, Channel Estimation, Imaging |
| [rvCSI](rvcsi-domain-model.md) | Edge RF sensing runtime: multi-source CSI ingestion, validation, normalization, event extraction, RuVector RF memory, agent/MCP integration | 7 contexts: Capture, Validation, Signal, Calibration, Event, Memory, Agent |
## How to read these