Adds an offline, dependency-free visualization for the drone training system:
a top-down swarm replay synced with training-metric curves, fed by a JSONL
telemetry log the trainer emits. No server, no build step, no CDN.
## Telemetry recorder (integration/telemetry.rs, always compiled, no new deps)
- TelemetryRecorder writes newline-delimited JSON: one `meta` (profile, area,
ground-truth victims), many `step` (per-tick drone x/y/heading/battery/detection
+ coverage%), and per-episode `episode` (mean_return, policy_loss, value_loss).
- Written by hand (no serde_json) so it stays in the default build; 2 tests.
## train_marl telemetry flags
- `--telemetry FILE` writes the log; `--telemetry-episode N` selects which
episode's spatial steps to record (metrics recorded for all episodes).
## Visualizer (viz/swarm_viz.html — single file, vanilla JS + canvas)
- LEFT: top-down replay — heading-oriented drone triangles (cyan/lime on
detection), victim markers, growing coverage heatmap, detection pulse rings,
play/pause/scrub/speed controls + live coverage/detection readout.
- RIGHT: three autoscaled line charts (mean return, policy loss, value loss)
over episodes, hand-drawn (no chart library).
- Loads via file picker/drag-drop or auto-fetches the bundled sample; dark
drone-ops theme; graceful degradation on file:// CORS.
- viz/sample_telemetry.jsonl: real 30-episode / 4-drone / 400×400 m run
(value_loss 20052→7154 — visible critic learning). Parses 1 meta / 60 step / 30 episode.
## Usage
cargo run --release -p ruview-swarm --features train,cuda --bin train_marl -- \
--episodes 5000 --telemetry run.jsonl
open v2/crates/ruview-swarm/viz/swarm_viz.html # load run.jsonl
Tests unchanged (91 default / 96 train / 104 ruflo+itar); telemetry adds 2.
Co-Authored-By: claude-flow <ruv@ruv.net>
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