mn-blueprints is a self-contained runnable MirrorNeuron workflow blueprint catalog. Each blueprint folder includes
its own manifest, configuration, payloads, README, and user-facing SPEC.md.
List available blueprints:
mn blueprint listRun a catalog blueprint:
mn run <blueprint_id>Run a checked-in folder directly:
cd <blueprint_id>
mn run --folder .Run repository tests:
python3 -m pytest -q| Blueprint | Category | Purpose |
|---|---|---|
adaptive_experiment_planning |
Science | Use this blueprint to choose the next experiment from prior yield, toxicity, cost, and confidence signals before spending lab capacity. |
ai_audit_readiness |
Security | Use this blueprint to turn AI and cyber control requirements into an evidence-backed readiness pack your team can review before audit or launch. |
ai_strategy_planning |
Business | Use this blueprint to turn messy discovery notes into a board-ready AI strategy recommendation with priorities, risks, and next steps. |
claim_risk_triage |
Finance | Use this blueprint to prioritize claim reviews by combining fraud signals, queue pressure, and adjuster capacity into an auditable triage recommendation. |
climate_resilience_planning_simulation |
Science | Use this blueprint to compare local flood mitigation plans as rainfall, water levels, pump capacity, and vulnerable assets change. |
closed_loop_agent_runtime |
Engineering | Use this blueprint to understand how a closed-loop agent observes changing work, decides on each tick, and leaves an inspectable action trail. |
cluster_reliability_simulation |
Engineering | Use this blueprint to test and demo advanced cluster reliability management with Nomad-inspired scheduling, lifecycle, recovery, drain, and service-discovery controls. |
codebase_memory_compression_analysis |
Engineering | Use this blueprint to see how compressed agent memory helps teams analyze large codebases without flooding every worker with full repository context. |
context_memory_audit |
Engineering | Use this blueprint to audit how role-specific context packets move through a multi-agent decision process and affect the final recommendation. |
context_memory_compression |
Engineering | Use this blueprint to test whether compressed working memory keeps a growing LLM workflow useful while reducing context load and cost. |
contract_negotiation_simulation |
Engineering | Use this blueprint to model buyer-supplier negotiation rounds and compare offers as demand, price, and capacity change. |
credit_default_warning |
Finance | Use this blueprint to spot borrower default pressure early and compare policy responses before credit risk turns into losses. |
customer_lifecycle_email_auto |
Business | Use this blueprint to plan, generate, check, send, and track lifecycle emails so customer outreach stays timely, governed, and tied to customer state. |
drug_discovery_simulation |
Science | Use this blueprint to run a multi-stage drug discovery loop that generates, filters, and evaluates candidates with reviewable evidence. |
ecosystem_simulation |
Science | Use this blueprint to explore ecosystem interventions across regions and compare population effects before making policy or field decisions. |
environment_control_simulation |
Engineering | Use this blueprint to experiment with control decisions in a changing environment where load, temperature, reserve, and service levels interact. |
event_stream_triage |
Engineering | Use this blueprint to triage noisy event streams and see how anomaly pressure, queue depth, and false positives change decisions over time. |
facility_safety_video_monitor |
Security | Use this blueprint to watch an approved camera stream, detect visible people, summarize what is observable, and raise safety alerts with a reviewable event trail. |
human_approval_gate |
Security | Use this blueprint to add a human approval checkpoint before an agent applies high-impact actions, with clear review and audit records. |
human_review_workflow |
Security | Use this blueprint to run a complete human review loop where requests, decisions, revisions, and applied actions are all captured. |
liquidity_risk_monitor |
Finance | Use this blueprint to monitor market microstructure signals and understand emerging liquidity risk before trades become expensive or fragile. |
live_telemetry_monitor |
Engineering | Use this blueprint to process live telemetry chunks, detect changing signal patterns, and summarize what operators need to notice. |
llm_tool_orchestration |
Engineering | Use this blueprint to see an LLM agent call a forecast tool, weigh the result, and choose a resource action you can inspect. |
message_routing_trace |
Engineering | Use this blueprint to trace how messages move through router and aggregator agents so workflow wiring is easier to debug and explain. |
motion_planning_simulation |
Science | Use this blueprint to visualize shared-world motion planning so you can inspect coordination, conflicts, and route choices between agents. |
native_live_monitor_service |
Engineering | Use this blueprint to run a lightweight native monitor that keeps producing decisions over live state until you stop it. |
network_threat_monitor |
security | This generated blueprint monitors network events, scores suspicious spamware/malware/hack behavior, and writes a dry-run alarm artifact for human review. |
openshell_sandbox_worker_pipeline |
Engineering | Use this blueprint to run shell and Python workers inside isolated execution boundaries while keeping each step traceable. |
outbreak_response_simulation |
Science | Use this blueprint to compare outbreak response policies as infections, mobility, vaccination, and hospital load evolve. |
parallel_worker_benchmark |
Engineering | Use this blueprint to stress-test broad parallel fan-out and measure how deterministic workers behave as runtime scale increases. |
policy_feedback_optimization_simulation |
Engineering | Use this blueprint to tune policy thresholds through repeated feedback so you can compare rewards, incidents, and tradeoffs before deployment. |
portfolio_crash_stress_simulation |
Finance | Use this blueprint to stress a portfolio against crash, rate, and liquidity shocks and review rebalancing choices before taking action. |
pricing_profit_simulation |
Business | Use this blueprint to compare pricing moves against demand, inventory, margin, and competitors before you change prices in the real world. |
python_sdk_research_pipeline |
Engineering | Use this blueprint to author a MirrorNeuron workflow directly in Python and compile it into a runnable blueprint bundle. |
python_sdk_research_service |
Engineering | Use this blueprint to run a Python-defined workflow as a long-lived research service with repeated stateful turns. |
revenue_retention_simulation |
Business | Use this blueprint to compare retention offers for at-risk customers and choose interventions with clear revenue, churn, and customer-experience tradeoffs. |
sandboxed_codegen_review |
Security | Use this blueprint to generate, review, and validate code inside a sandboxed LLM loop before trusting the result. |
service_capacity_simulation |
Business | Use this blueprint to test staffing, deflection, and escalation decisions before service queues miss SLA targets. |
state_audit_simulation |
Engineering | Use this blueprint to record simulation state changes so every agent decision can be inspected after the run. |
stream_backpressure_simulation |
Engineering | Use this blueprint to observe bounded queues, slow workers, and retry-later behavior before building live stream workflows. |
supply_chain_resilience_simulation |
Business | Use this blueprint to rehearse supplier disruption responses and choose actions that protect inventory, fulfillment, and customer service levels. |
traffic_control_simulation |
Science | Use this blueprint to test traffic signal and rerouting controls against speed, incident, volume, and emissions tradeoffs. |
user_activity_rmf_triage |
general | A local security worker that watches user activity, detects suspicious behavior, asks risky sessions to re-authenticate, and writes RMF/ATO/cATO-ready evidence artifacts. |
vendor_selection_decision |
Business | Use this blueprint to convert requirements and vendor responses into a scored recommendation, implementation plan, and reviewable decision record. |
zip_code_property_memory_ranking |
Finance | Use this blueprint to rank property opportunities while preserving useful deal memory across noisy ZIP-code history, broker flow, financing constraints, and past outcomes. |
zip_code_property_ranking |
Finance | Use this blueprint to rank property acquisition opportunities by ZIP-code demand, price, cap-rate, and risk signals before committing diligence time. |
Most blueprint folders contain:
| Path | Purpose |
|---|---|
README.md |
Self-contained quickstart, inspection notes, and validation guidance. |
SPEC.md |
User-facing problem, outcome, evaluation criteria, limits, and upgrade path. |
TERM.md |
Terms, assumptions, or domain notes when present. |
manifest.json |
Runtime graph, entrypoints, metadata, runners, services, and environment access. |
config/default.json |
Default launch configuration and mock/sample inputs. |
config/overwrite.json |
Optional local overrides. Do not commit customer secrets. |
payloads/ |
Worker code, prompts, policies, fixtures, and support files. |
- Review
manifest.json,payloads/, andpass_envbefore live runs. - Start with mock, dry-run, or quick-test settings before enabling real external services.
- Keep customer-specific inputs and secrets in local overrides or environment variables.
- Update the local blueprint README and
SPEC.mdwhen behavior, inputs, outputs, or limits change.