Adds the RQ3 agent-selector backend as a reproducible, offline measurement
decision — not relay/data-plane traffic. Containment is untouched: the model
query is a local call to localhost:11434.
- selector.py: SelectorPolicy ABC seam; static/random/agent(heuristic) built-ins;
make_policy() resolves (strategy, agent_backend); run_selection writes a
write-once selector.json provenance sidecar.
- agent_selector.py: OllamaAgentPolicy — reproducible confirmatory arm
(temp=0 + per-run seed, decisions cached keyed by (seed, state-hash),
deterministic heuristic fallback on any model/parse failure, model weights
digest pinned for the manifest). ClaudeExploratoryPolicy — EXPLORATORY-only
stub: makes no paid call, refuses to serve as a confirmatory backend.
- provenance.py: additive selector_backend field so an agent-selected run pins
the exact model id + weights digest.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
churn.py emits a seed-deterministic kill/spawn schedule (pure data — no real VM
spin/kill; the live fabric half stays gated by the containment law). selector.py
consumes the schedule and rebuilds a circuit whenever a kill drops one of its
hops, across static | random | agent strategies; the paid frontier-model agent
arm (GOAL envelope (c)) is human-gated and NOT wired — the agent strategy here is
a local stability heuristic that spends nothing. analysis/metrics.py aggregates
the four DV families (RQ1 correlation AUC, RQ2 entropy bits, RQ3 throughput
retention + rebuild-classifier AUC) into a schema-valid, write-once metrics.json.
Acceptance check green: under a fixed churn seed the selector rebuilds every
dropped circuit (every_drop_rebuilt, all strategies) and metrics.json is
produced. Python R7 selector suite 11 passed; full SOR suite 92 passed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
leetcrypt