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Affaan Mustafa
726972d735
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.