{"engine":"ghostbrand.multi_agent_registry.v1","doctrine":"Specialist agents collaborate via 6 orchestration patterns (IBM watsonx + Google Antigravity aligned). Roles are explicit, inputs/outputs formal, cadence declared.","roles_summary":{"ORCHESTRATOR":1,"SPECIALIST":9,"AUDITOR":4,"EXECUTOR":3},"n_agents":17,"n_patterns":6,"agents":[{"id":"ORCHESTRATOR_AUTONOMY_CORE","role":"ORCHESTRATOR","module":"autonomy_core.py","responsibilities":["Run autonomy_cycle every N minutes","Invoke specialists in correct order (phases 4.86-4.114)","Seal Merkle-chain handoff after each cycle","Trigger self_resolver for pending questions"],"reads_from":["all collections"],"writes_to":["autonomy_runs","handoff_snapshots"],"cadence":"every 30min"},{"id":"SPECIALIST_PRICING","role":"SPECIALIST","module":"pricing_optimizer.py","domain":"revenue","math":"MLE demand + Thompson anchor","inputs":["pricing_history"],"outputs":["optimal_price","anchor_multiplier"]},{"id":"SPECIALIST_ATTRIBUTION","role":"SPECIALIST","module":"agents/attribution.py","domain":"measurement","math":"Markov chain removal effect","inputs":["journeys"],"outputs":["attribution_per_channel"]},{"id":"SPECIALIST_CLV","role":"SPECIALIST","module":"agents/ltv.py","domain":"measurement","math":"BG/NBD + Gamma-Gamma","inputs":["customer_history"],"outputs":["per_customer_clv","portfolio_clv"]},{"id":"SPECIALIST_MMM","role":"SPECIALIST","module":"agents/mmm.py","domain":"measurement","math":"Adstock + Hill + Ridge regression","inputs":["response_ts","channels_ts"],"outputs":["channel_contributions","marginal_roas"]},{"id":"SPECIALIST_BANDIT","role":"SPECIALIST","module":"agents/bandit.py","domain":"allocation","math":"Thompson Sampling + fractional Kelly","inputs":["channel_stats","budget"],"outputs":["allocations"]},{"id":"SPECIALIST_COMPLIANCE","role":"SPECIALIST","module":"compliance_filter.py","domain":"brand","math":"density-aware banned phrase + strong signals bonus","inputs":["text"],"outputs":["score","verdict"]},{"id":"AUDITOR_DIDEROT","role":"AUDITOR","module":"diderot_evaluator.py","function":"Score every decision on math rigor (>= 0.65 to execute)","reads_from":["decisions","math_params"],"writes_to":["diderot_scores"]},{"id":"AUDITOR_SURVIVAL","role":"AUDITOR","module":"survival_axiom.py","function":"Hard gate per spending action (AX-1 enforcement)","reads_from":["system_state","survival_metrics"],"writes_to":["axiom_rejections","axiom_stats"]},{"id":"AUDITOR_CAPABILITIES","role":"AUDITOR","module":"capabilities_registry.py","function":"Snapshot of all configured integrations — anti-leak (AX-2)","reads_from":["os.environ","credentials","external_setup_state"]},{"id":"AUDITOR_BOOTSTRAP","role":"AUDITOR","module":"agent_bootstrap.py","function":"8-check gate every new agent must pass before acting"},{"id":"EXECUTOR_CHECKOUT","role":"EXECUTOR","module":"payment_router.py","function":"Build checkout URL via Wompi or LemonSqueezy"},{"id":"EXECUTOR_WHATSAPP","role":"EXECUTOR","module":"whatsapp_sender.py","function":"Send Meta Cloud API template messages"},{"id":"EXECUTOR_SELF_RESOLVER","role":"EXECUTOR","module":"self_question_resolver.py","function":"Auto-answer math-resolvable questions (AX-4)"},{"id":"SPECIALIST_BEHAVIORAL_SEG","role":"SPECIALIST","module":"behavioral_segmentation.py","domain":"measurement","math":"Weighted linear intent + bucket map","inputs":["behavioral_events"],"outputs":["intent_score","bucket","next_best_action"]},{"id":"SPECIALIST_MARKET_RESEARCH","role":"SPECIALIST","module":"market_research_synthesizer.py","domain":"intelligence","math":"LLM synthesis + citation-density + compliance gate","inputs":["query","vertical"],"outputs":["synthesis_text","citations","verdict"]},{"id":"SPECIALIST_FINANCIAL_MODEL","role":"SPECIALIST","module":"financial_model.py","domain":"finance","math":"Driver-based Monte Carlo (LogNormal visitors × Beta CVR × Beta churn)","inputs":["starting_cash","channels_drivers","costs","weeks"],"outputs":["p_survival","cash_p10_p50_p90_trajectory","verdict_GO_CAUTION_REDESIGN"]}],"orchestration_patterns":{"SEQUENTIAL_HIERARCHICAL":{"example":"autonomy_cycle: scout -> pricing -> creator -> qa -> kaizen","use_when":"order matters, each step depends on previous output"},"PARALLEL_DELEGATION":{"example":"parallel_fronts.py: Thompson + Kelly distributes budget across independent verticals simultaneously","use_when":"subtasks are independent; max 45% handoff reduction (IBM)"},"DYNAMIC_ROUTING":{"example":"self_question_resolver: classify(q) -> resolver[cat](q)","use_when":"input type varies; router dispatches to specialist"},"HANDOFF_PEER_TO_PEER":{"example":"Merkle-chain handoff between agent sessions — context passes cryptographically without central return","use_when":"agent-to-agent transfer; zero-loss required"},"SHARED_MEMORY_BLACKBOARD":{"example":"incoming_info_processor writes -> implementation_queue / improvement_plan -> autonomy_cycle reads","use_when":"incremental collaboration; multiple writers + reader"},"SWARM":{"example":"agents/*.py as lightweight pure functions with JSON IO","use_when":"scalable decentralized; no central bottleneck"}},"references":["IBM watsonx Orchestrate + ToolSmith (2026)","Google Antigravity + Gemini 3 Agentic Coding (Nov 2025)","HyperAgents meta-editable improvement (2026)","SAGE RL self-evolution + persistent libraries"]}