The moat layer: spatial deconfliction for multiple agents (and humans) on one
codebase, modeled on aircraft TCAS — measure how close two agents are in
code-space, then transmit-intent (Traffic Advisory) and steer-away (Resolution
Advisory) before they collide at the git layer.
scripts/lib/agent-proximity/:
- distance.js — the math: per-channel collision probabilities combined via
noisy-OR R = 1 - Π(1 - ω·r). Channels: edit overlap (file + line-range
Jaccard), dependency coupling (γ^(d-1) over the import graph, direction-
agnostic — catches 'edit there breaks here' even when tree-distant), and tree
proximity (LCA-based, soft prior). TCAS advise(): clear / advisory(transmit) /
resolution(steer), with deterministic right-of-way priority so the maneuver is
coordinated. closureRate() for approach-speed escalation.
- graph.js — lightweight require/import dependency-graph builder (fs or in-memory).
- index.js — scanAirspace(): pairwise advisories + 3D vector embedding (space-
filling path embedding pulled toward dependency neighbours) so a 'where are
the agents' visualization can render the file-cloud and watch agents crawl /
steer.
docs/design/agent-proximity.md — full mathematical formulation + protocol + viz
+ roadmap (v1 call-graph/symbol channels + live session-diff wiring; v2 cross-
machine airspace over Tailscale, the zero-conflict-swarm demo).
17 tests; full suite 2869/2869; lint green.
