Agentic Framework Benchmark and Evaluation Standard
Defines a reproducible benchmark for agent frameworks, including orchestration, memory, tools, safety boundaries, observability, durability, interoperability, and evidence-backed evaluation.
Library / Canonical series
Permanent candidate standards across 26 engineering domains, each with normalized control IDs, evidence requirements, and assessment procedures.
Assessment doctrine
Implementation intent, minimum and advanced implementation, evidence requirements, assessment procedures, metrics, exceptions, and compensating controls.
The permanent design, editorial, evidence, control, assessment, taxonomy, and QA conventions inherited by every later publication.
Visual language: Control lattices, evidence chains, and assessment matrices.
Network engineering and cybersecurity standards, from topology and source of truth to zero trust and detection.
Visual language: Topology, routing and state graphs, trust zones, packet and control flows, attack paths, enforcement boundaries, and evidence chains.
Software engineering, platform engineering, distributed systems, database and storage, and reliability engineering.
Visual language: Dependency graphs, pipelines, state machines, event streams, service topology, failure propagation, SLOs, and recovery paths.
Artificial intelligence, knowledge and grounding, data and evidence, identity, and learning.
Visual language: Model routing lattices, knowledge graphs, provenance flows, identity trust paths, policy gates, and learning loops.
Cloud, endpoint, operational technology, telecommunications, hardware, IoT, realtime media, and web runtime.
Visual language: Cloud planes, endpoint trust, OT zones, radio layers, compute fabrics, sensor graphs, media paths, and runtime isolation.
Emerging technology, quantum technology, and physical AI and robotics.
Visual language: Readiness horizons, quantum state flows, photonic interconnects, spiking graphs, and physical-AI feedback loops.
Governance, risk, and compliance, and user experience and human-system interaction.
Visual language: Control maps, decision trees, risk matrices, and interaction flows.
Catalog
Defines a reproducible benchmark for agent frameworks, including orchestration, memory, tools, safety boundaries, observability, durability, interoperability, and evidence-backed evaluation.
Defines model selection, training, evaluation, packaging, deployment, inference, governance, and lifecycle requirements for production AI systems.
Defines evaluation of language-model quality, grounding, reasoning, retrieval, hallucination resistance, multilingual behavior, and task-specific natural-language performance.
Defines benchmarks for AI-assisted software engineering, including code generation, repository reasoning, testing, repair, security, and autonomous engineering workflows.
Defines evaluation of AI systems performing infrastructure automation and infrastructure-as-code tasks, emphasizing correctness, safety, rollback, policy, and reproducibility.
Defines alignment and adversarial evaluation for AI systems, including red-team methodology, instruction hierarchy, sycophancy, deception, unsafe autonomy, and behavioral assurance.
Defines context engineering, trajectory compaction, temporal memory, retrieval, persistence, and context-window governance for long-running agentic systems.
Defines latency, synchronization, quality, safety, and evaluation requirements for multimodal AI spanning vision, voice, streaming interaction, and realtime user experience.
Defines governed fine-tuning, reinforcement learning from evaluative feedback, synthetic-data generation, dataset provenance, contamination controls, and post-training validation.
Defines identity, consent, provenance, safety, continuity, and lifecycle requirements for AI personas, avatars, synthetic voices, and persistent user-facing characters.
Defines architecture and evaluation for mixture-of-experts and state-space models, including routing, sparsity, memory, throughput, scaling, and deployment tradeoffs.
Defines neuro-symbolic and continual-learning architectures that combine learned models with explicit reasoning while controlling catastrophic forgetting and knowledge drift.
Defines AI-assisted engineering workflows and model-routing strategies across planning, coding, review, testing, tool use, escalation, and cost-aware execution.
Defines production inference serving, quantization, batching, KV-cache management, accelerator utilization, latency, throughput, and quality-preservation requirements.
Defines federated and privacy-preserving machine learning, including local training, aggregation, differential privacy, secure computation, model leakage, and governance.
Defines multi-cloud architecture, landing zones, control planes, identity, policy, networking, observability, portability, sovereignty, and cross-cloud governance.
Defines AWS architecture, security, automation, identity, networking, observability, resilience, cost governance, and evidence requirements for enterprise workloads.
Defines Microsoft Azure architecture, security, automation, identity, networking, observability, resilience, and policy-driven enterprise operation.
Defines Google Cloud architecture and automation across organizations, IAM, networking, workload platforms, observability, resilience, and policy enforcement.
Defines Oracle Cloud architecture and automation across tenancy, IAM, networking, compute, data services, resilience, security, and operational governance.
Defines Alibaba Cloud architecture and automation across accounts, identity, networking, compute, security, observability, resilience, and regional considerations.
Defines Kubernetes and container-orchestration architecture, operators, policy, multitenancy, networking, workload identity, supply chain, observability, and lifecycle control.
Defines serverless and event-driven compute, including functions, triggers, state, idempotency, security, scaling, observability, portability, and cost behavior.
Defines decentralized physical infrastructure networks as a compute and infrastructure model, including trust, incentives, workload placement, verification, privacy, and risk.
Defines private-cloud, hypervisor, and bare-metal architecture across virtualization, isolation, provisioning, storage, networking, lifecycle, resilience, and trusted operation.
Defines Web3 and decentralized-ledger architecture, including consensus, keys, smart contracts, off-chain integration, privacy, governance, and operational risk.
Defines cryptographic inventory, agility, approved algorithms, hybrid migration, testing, and lifecycle.
Defines software and AI component inventories, attestations, signing, trust, and verification.
Defines continuous authorization, least privilege, separation of duties, capability grants, and evidence.
Defines trust boundaries, threat modeling, secure defaults, isolation, resilience, and assurance.
Defines security workflow automation, approvals, evidence, testing, failure handling, and oversight.
Defines firewall policy design, lifecycle, NAT, segmentation, change safety, and validation.
Defines secure zones, identity-aware policy, workload isolation, enforcement, and verification.
Defines discovery, risk, prioritization, remediation, exceptions, proof, and metrics.
Defines TEEs, attestation, threat models, secrets, deployment, evidence, and limitations.
Defines FHE and ZKP applicability, design, implementation, performance, threat models, and validation.
Defines API authorization, tokens, scopes, rotation, validation, monitoring, and revocation.
Defines isolation, images, runtime, orchestration, patching, policy, and monitoring.
Defines controlled adversary techniques, validation boundaries, evidence, and remediation for web and clients.
Defines controlled techniques and assurance for networks, wireless systems, and supply chains.
Defines authorization, scope, methodology, safety, evidence, reporting, remediation, and retest.
Defines telemetry, detection lifecycle, hunting, testing, metrics, evidence, and operations.
Defines exposed services, segmentation, access, inspection, monitoring, resilience, and validation.
Defines vector storage and local-first synchronization for AI and distributed applications, including embeddings, indexing, replication, conflict handling, and offline operation.
Defines OpenTelemetry-aligned observability semantics for models and agents, covering traces, tool calls, prompts, tokens, latency, cost, errors, and privacy-safe telemetry.
Defines data-sovereignty, privacy-preservation, residency, classification, egress control, minimization, and policy enforcement across local, cloud, and hybrid systems.
Defines event sourcing, CQRS, durable state machines, replay, idempotency, ordering, reconciliation, and evidence-preserving state transitions.
Defines tamper-evident ledgers and evidence bundles using cryptographic linking, provenance, signatures, retention, verification, and chain-of-custody controls.
Workload-aligned persistence, transactional integrity, graph traversal, time-series operations, and governed polyglot persistence.
Storage tiering, indexing and search, backup integrity, recovery validation, retention, and evidence-driven data protection.
Tenant isolation, data access zones, authorization boundaries, encryption context, residency, and controlled analytical access.
Durable execution, message delivery semantics, idempotency, compensation, event ordering, and recoverable distributed workflows.
Versioned API contracts, RPC semantics, service-mesh boundaries, compatibility, resilience, and observable service communication.
Defines WebAssembly and edge-execution sandboxes, including component boundaries, capability security, portability, resource controls, isolation, observability, and deployment governance.
Defines sovereign and air-gapped AI deployment, including offline model operation, controlled updates, local inference, evidence, data sovereignty, and disconnected lifecycle management.
Defines neuromorphic and NPU-based computing, including accelerator architecture, workload suitability, programming models, energy efficiency, benchmarking, and adoption constraints.
Defines silicon photonics and next-generation interconnects, including optical I/O, co-packaging, topology, power, thermal behavior, interoperability, reliability, and readiness assessment.
Standard in the Emerging Technology collection of the MYTHOS Engineering Standards Library.
Standard in the Emerging Technology collection of the MYTHOS Engineering Standards Library.
Standard in the Emerging Technology collection of the MYTHOS Engineering Standards Library.
Defines managed endpoint architecture across operating systems, configuration baselines, MDM/UEM, patching, application control, identity, telemetry, isolation, and fleet lifecycle.
Govern product intent before implementation: evidence, scope, requirements, invariants, risk, and objective acceptance.
Treat documentation as an engineered authority, evidence, traceability, and lifecycle system.
Engineer security, privacy, and trust as system properties with explicit authority, isolation, evidence, and resilience.
Turn requirements, hazards, and production behavior into reproducible verification and validation evidence.
Govern readiness, release, operation, recovery, maintenance, deprecation, and retirement as one lifecycle.
Make data meaning, contracts, interfaces, events, lineage, reliability, and compatibility explicit and testable.
Design human interfaces that preserve understanding, accessibility, authority, safety, feedback, and recovery.
Govern extensions, plugins, publishers, provenance, admission, capabilities, isolation, updates, and revocation.
Govern material AI behavior through justified use, impact analysis, evaluation, grounding, human control, and lifecycle evidence.
Bound delegated action with mission contracts, policy, tool controls, memory governance, budgets, evidence, verification, and containment.
Defines governance for federal, defense, sovereign, and regulated environments, including control applicability, evidence, authorization boundaries, supply chain, residency, and compliance traceability.
Defines AI governance, privacy, and risk management across model lifecycle, data use, transparency, human oversight, safety, incident response, accountability, and regulatory alignment.
Defines AI GPU server and cluster architecture across accelerators, memory, interconnects, storage, power, cooling, scheduling, observability, reliability, and lifecycle planning.
Defines trusted compute, DPUs, firmware, secure boot, attestation, root of trust, hardware isolation, update integrity, and low-level platform assurance.
Defines interoperable identity for humans, workloads, agents, and services, including authentication, attestation, delegation, ephemeral credentials, and lifecycle governance.
Defines PKI and attribute-based access control, including certificate lifecycle, trust anchors, policy attributes, authorization decisions, revocation, and auditability.
Defines IoT and edge-sensor architecture across Matter, device identity, onboarding, telemetry, local processing, radio connectivity, update security, privacy, and lifecycle management.
Defines retrieval-augmented generation, source authority, grounding, citation, provenance, freshness, conflict resolution, and evidence requirements for knowledge-backed AI.
Defines persistent persona and memory architecture, including memory classes, retention, consent, retrieval, identity continuity, summarization, and user control.
Defines adaptive learning, skill graphs, labs, cyber ranges, competency evidence, personalized progression, safe simulation, and workforce-assurance measurement.
Defines architecture views, topology, requirements, resilience, scale, documentation, and acceptance.
Defines automation contracts, data models, idempotency, validation, rollback, evidence, and vendor abstraction.
Defines topology models, simulations, reachability, differential testing, evidence, and confidence.
Defines identity-aware networking, segmentation, enforcement, telemetry, and continuous validation.
Defines authoritative state, discovery, intent, reconciliation, exceptions, and audit.
Defines SR-MPLS, SRv6, policy, traffic engineering, operations, migration, and security.
Defines mobile architecture, orchestration, slicing, isolation, QoS, telemetry, and research boundaries.
Defines structured troubleshooting, telemetry, packet analysis, isolation, validation, and closure evidence.
Defines cabling, optics, facilities interfaces, topology, labeling, testing, and lifecycle.
Defines routing architecture, naming, addressing, DDI, policy, operations, and assurance.
Defines access switching, 802.1X, profiling, wireless design, RF, roaming, and validation.
Defines secure ICS and critical-infrastructure architecture, emphasizing safety, segmentation, remote access, asset visibility, protocol constraints, monitoring, recovery, and change control.
Defines physical AI and autonomous fleets across perception, sensor fusion, planning, control, safety, simulation, human oversight, fleet operations, evidence, and fail-safe behavior.
Standard in the Physical AI and Robotics collection of the MYTHOS Engineering Standards Library.
Standard in the Physical AI and Robotics collection of the MYTHOS Engineering Standards Library.
Standard in the Physical AI and Robotics collection of the MYTHOS Engineering Standards Library.
Standard in the Physical AI and Robotics collection of the MYTHOS Engineering Standards Library.
Standard in the Physical AI and Robotics collection of the MYTHOS Engineering Standards Library.
Reproducible builds, artifact provenance, controlled promotion, software supply-chain assurance, and evidence-bearing releases.
Declarative desired state, plan review, drift control, provider governance, secret-safe automation, and reversible infrastructure change.
Golden paths, self-service platforms, GitOps reconciliation, policy enforcement, developer experience, and platform product management.
Evidence-driven selection and governance of managed platforms, hosted runtimes, agent services, and external control planes.
Lifecycle intelligence, supportability, refresh planning, compatibility management, technical debt, and controlled retirement.
Governed extension discovery, trust tiers, package integrity, compatibility, monetization boundaries, and marketplace operations.
Defines quantum-computing benchmark and algorithm evaluation, distinguishing theoretical advantage from reproducible hardware results, noise effects, simulation, and operational readiness.
Defines quantum-network architecture and security, including quantum channels, classical coordination, repeaters, trust, routing, control, interoperability, and deployment constraints.
Defines quantum key distribution and entanglement networking, including protocol assumptions, key management, monitoring, integration, security limitations, and evidence requirements.
Standard in the Quantum Technology collection of the MYTHOS Engineering Standards Library.
Standard in the Quantum Technology collection of the MYTHOS Engineering Standards Library.
Standard in the Quantum Technology collection of the MYTHOS Engineering Standards Library.
Defines realtime voice and WebRTC systems, including signaling, media transport, latency, quality, identity, synthetic-media provenance, recording, privacy, and abuse controls.
Service objectives, error-budget governance, capacity models, demand forecasting, and reliability investment decisions.
Failure-domain architecture, recovery objectives, multi-region design, restore validation, game days, and crisis readiness.
Unit economics, token and compute cost, capacity efficiency, carbon-aware operation, and value-based engineering governance.
Domain boundaries, invariant-rich models, typed contracts, and architecture that keeps frameworks subordinate to business meaning.
Memory-safe systems engineering, explicit ownership, controlled unsafe code, concurrency correctness, and production Rust governance.
Simple service boundaries, goroutine lifecycle discipline, backpressure, cancellation, observability, and operable Go systems.
Typed Python, deterministic automation, dependency control, testability, packaging, and maintainable scripting at enterprise scale.
Explicit language boundaries, schema-governed messages, compatibility policy, local IPC, remote RPC, and failure containment.
Secure desktop runtimes, Rust-native command boundaries, Svelte application state, capability control, and update integrity.
Executable specifications, invariant verification, deterministic transitions, model checking, and traceable implementation refinement.
Semantic intent payloads, typed renderers, deterministic presentation, accessibility, and model-independent interface contracts.
Debuggability by design, fault injection, property testing, reproducible failure analysis, and resilient recovery behavior.
Defines 5G/6G core, Open RAN, slicing, orchestration, identity, transport, telemetry, assurance, and security for programmable telecommunications infrastructure.
Defines distributed antenna systems and indoor RF engineering, including coverage, capacity, spectrum, interference, testing, monitoring, and lifecycle governance.
Defines enterprise telephony and VoIP architecture across call control, SIP, media, emergency calling, QoS, survivability, security, monitoring, and lifecycle management.
Defines AI-native interface design for dense technical systems, including accessibility, information hierarchy, explainability, adaptive interaction, keyboard operation, and human factors.
Defines human-in-the-loop approval workflows, including risk-tiered intervention, immutable approval context, delegation, escalation, timeout, revocation, and evidence of consent.
Defines the Mythos cyberpunk-noir visual system as a controlled design language for state, hierarchy, contrast, motion, density, legibility, and accessibility rather than decoration alone.
Defines spatial-computing and WebGPU/wgpu integration for immersive technical interfaces, including rendering, interaction, accessibility, performance, data visualization, and device fallback.
Defines secure browser compute using WebGPU and browser-local AI, including isolation, model execution, data boundaries, capability control, performance, privacy, and fallback behavior.
Candidate status describes publication review state. It does not establish certification, legal compliance, implementation conformance, benchmark reproduction, or product readiness.