mcorbett51090

by Matt Corbett

Chaos-engineering & resilience team — agents that make distributed systems survive failure. resilience-architect owns the DESIGN side: failure-mode analysis (FMEA), resilience patterns (timeouts, retries with backoff+jitter, bulkheads, circuit breakers, load shedding, graceful degradation, idempotency), the observability-maturity gate for whether you're ready to run chaos, and redundancy/DR (multi-AZ/region, failover, RTO/RPO). chaos-experiment-engineer owns the EXPERIMENT + VERIFICATION side: hypothesis-driven experiments, blast-radius containment (automatic abort/rollback), game days, fault injection (latency/error/resource/dependency-outage/partition/zone), and verifying the pattern held under load+fault. skills, a knowledge bank (decision trees + a dated 2026 patterns reference), templates. Distinct from observability-sre (metrics/SLO/on-call — a hard prerequisite), devops-cicd (progressive delivery), performance-engineering (load), incident-response-dfir. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Childcare / early-education center operations team — agents (childcare-center-lead, enrollment-and-family-manager, classroom-ratio-compliance-advisor) for the three engines of an early-education center: the operations & tuition model (enrollment/waitlist, capacity vs licensed ratios, staffing to ratio, family retention, P&L), the enrollment & family funnel (tour-to-enroll conversion, waitlist, paperwork, family communication, tuition & CCDF/state subsidy billing), and ratio & licensing compliance (ratio and group-size by age, licensing readiness, staff qualifications, health & safety, incident documentation). skills, a decision-tree knowledge bank (Mermaid trees + a dated 2026 reference), best-practices, templates, commands. ADVISORY operations knowledge, not legal, licensing, or financial advice; state-specific ratios, group sizes, and subsidy rules are volatile and carry a retrieval date + verify-at-use; no child or family PII. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Chiropractic practice operations & compliance team — agents (chiropractic-practice-lead, chiro-billing-compliance-specialist) across the two engines of a DC office: the practice (capacity & scheduling to the care plan, the cash / insurance / wellness-plan model, membership pricing, patient-visit-average & plan-completion retention) and coding/compliance (CMT vs E&M by region, documented medical necessity via the PART exam, the active-vs-maintenance plateau call, ABN workflow, audit-defensible notes). skills, a decision-tree knowledge bank (a billing-and-medical-necessity Mermaid tree + a dated 2026 payer/coding reference), best-practices. Operations & coding decision-support, NOT medical/legal/billing advice and NOT a coding certification; no PHI; scope/coverage/coding rules are state/payer-specific + volatile — retrieval-dated + verify-at-use, flagged for a licensed professional. Seams: physical-therapy-rehab-clinic, medical-revenue-cycle. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Claude app-engineering specialist team — agents (claude-solution-architect, prompt-and-context-engineer, mcp-and-server-tools-engineer, agent-sdk-engineer, eval-engineer, claude-app-ops-engineer) for building production applications on the Claude API, the Claude Agent SDK, and MCP. Covers the build-surface decision (Messages API / Agent SDK / Managed Agents), model right-sizing (Opus 4.8 / Sonnet 4.6 / Haiku 4.5, 1M context), prompt caching, tool use + structured output, MCP server authoring + Anthropic-hosted server tools (computer use, code execution, Files API, memory), evals (golden sets, LLM-as-judge), and FinOps + reliability (batch, model routing, backoff, observability). dated-and-cited knowledge bank, templates, an advisory hook (house opinions). Seams: prompt-as-artifact, security, and cross-domain architecture escalate to ravenclaude-core. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

CLI-tooling-engineering team — agents (cli-architect, cli-implementation-engineer, tui-engineer, cli-distribution-engineer) for command-line tools and TUIs that feel native to the shell: the command/subcommand + flag/positional surface, config precedence (flags > env > file > default), the output contract (human by default, --json on demand, exit codes as an API, data->stdout/diagnostics->stderr, NO_COLOR/TTY detection), stdin, signal handling, TUIs (Ink / Bubble Tea / Textual / ratatui) with a non-TTY fallback, shell completions, and distribution (single static binary, Homebrew / Scoop / winget / npm / pipx, --version + update path). skills, a knowledge bank (command-surface + output/exit-code + framework + distribution decision trees + a dated 2026 map), best-practices, templates, commands, an advisory hook. Seams: service logic -> backend-engineering, release/signing -> devops-cicd, GUI sibling -> desktop-app-engineering, docs -> technical-writing-docs. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Clinical Trials specialist team — agents (trials-engagement-lead, protocol-design-specialist, clinical-operations-manager, regulatory-submissions-specialist), skills, templates, commands, an advisory hook, best-practice rules, and a research-grounded knowledge bank. A clinical-operations team for a sponsor, CRO, or site network — it designs feasible protocols (because eligibility criteria drive the enrollment failure that hits two-thirds of sites), plans patient recruitment against a ~$6,533 per-patient cost (and ~$19,533 to replace), manages site activation and the ~30% dropout, and frames the regulatory submission the way a study where 80% run late demands. Inherits ravenclaude-core protocols.

by Matt Corbett

Cloud-native & Kubernetes team — agents (kubernetes-architect, container-build-engineer, k8s-platform-operator, service-mesh-networking-engineer) for running workloads on Kubernetes well: workload design (Deployment/StatefulSet/Job, probes, requests/limits, PDBs, HPA/VPA), container build hygiene (minimal non-root images, distroless, multi-stage), platform ops (namespaces, RBAC, network policies, resource quotas, admission control, upgrades), and service-mesh networking (ingress/gateway, mTLS, traffic-splitting, observability). Cloud-agnostic. skills, a decision-tree knowledge bank (workload-type + ingress trees + a dated 2026 ecosystem map), best-practices, templates, commands, an advisory hook. Seams: managed control plane (AKS/EKS/GKE) -> azure/aws/gcp-cloud, GitOps reconcile -> devops-cicd, telemetry/SLOs -> observability-sre. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Commercial Real Estate specialist team — agents (cre-engagement-lead, acquisitions-underwriter, asset-property-manager, cre-market-analyst), skills, templates, commands, an advisory hook, best-practice rules, and a research-grounded knowledge bank. An acquisitions-and-asset-management team for a CRE owner, operator, or advisor — it underwrites a deal to in-place NOI, prices the cap-rate-vs-Treasury spread, reads the bifurcated vacancy, decomposes net effective rent, and stress-tests the debt and refinance wall before a board sees the IC memo. Inherits ravenclaude-core protocols.

by Matt Corbett

Computer-vision engineering team — agents for a production vision build: cv-systems-architect (task framing across classification / detection / segmentation / OCR / tracking / VLM, data & annotation strategy, build-vs-API and deployment-target choice, eval-metric design — mAP / IoU / precision-recall), cv-model-engineer (dataset curation, augmentation, transfer learning, model selection across YOLO / DETR / SAM / CLIP / ViT, active learning, the eval harness, drift), and vision-deployment-engineer (quantization / distillation, ONNX / TensorRT / CoreML / TFLite export, edge/embedded targets, streaming-video pipelines, latency). Vision-specific vs the MLOps-broad ml-engineering. Ships skills, a knowledge bank (Mermaid decision trees + a dated 2026 reference), best-practices, templates, commands. Engineering judgment, not a benchmark verdict; model/hardware/runtime specifics carry a retrieval date + [verify-at-use]; no PII, no image data stored. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

General-contractor project delivery team — agents covering the full GC lifecycle: project P&L/billing/closeout (gc-project-lead), takeoff/bid assembly/markup (estimating-and-takeoff-analyst), CPM scheduling/critical-path/float (scheduling-engineer), submittal log/RFIs/change-order process (submittal-rfi-coordinator), and jobsite safety/JHA/OSHA hazard prevention (jobsite-safety-advisor). Ships skills (estimating-and-bidding, cpm-scheduling, submittals-rfis-change-orders), commands, templates, a decision-tree knowledge bank, best-practices, an advisory anti-pattern hook, and a stdlib calculator. Inherits ravenclaude-core protocols.

by Matt Corbett

Conversational voice-AI engineering team — agents for production real-time voice agents: voice-ai-architect (cascade STT->LLM->TTS vs speech-to-speech, the latency budget, turn-taking / barge-in / endpointing, channel choice, build-vs-platform across Twilio / Vapi / Retell / LiveKit / Pipecat, guardrails), speech-pipeline-engineer (ASR & TTS provider choice, streaming transcription, VAD/endpointing, diarization, prosody/SSML, codecs, noise, WER), and dialog-and-integration-engineer (state, LLM orchestration and mid-call tool calling, SIP/PSTN telephony, IVR/DTMF, call routing, flow testing and eval). Ships skills, a knowledge bank (Mermaid decision trees + a dated 2026 reference), best-practices, templates, commands. Engineering judgment, not legal/compliance advice; the ASR/TTS/platform/telephony landscape is volatile — versions and latency numbers carry a retrieval date + [verify-at-use]; no PII, and call audio/transcripts are sensitive. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Corporate Development & M&A team — agents (corpdev-lead, ma-diligence-lead, integration-pmi-strategist), skills, commands, an advisory hook, best-practice rules, and a research-grounded knowledge bank. A buy-side deal team for a corp-dev, strategy, or finance lead: it frames the deal thesis before the model, triangulates valuation (DCF + trading comps + precedent transactions), runs diligence to confirm or kill the thesis, and prices integration risk pre-signing. Decision-support, not legal, tax, accounting, or a fairness opinion; multiples/comps/regulatory specifics are volatile + jurisdictional, retrieval-dated + verify-at-use; no MNPI. Distinct from startup-fundraising, finance, and treasury-management. Inherits ravenclaude-core protocols. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Craft-beverage (winery / brewery / distillery) operations team — agents (craft-beverage-operations-lead, tasting-room-and-club-manager, beverage-distribution-compliance-advisor) across the three engines of a producer: production & cost (batch/yield planning, COGS per unit, tank/barrel/time capacity, packaging, channel margin mix), the tasting room & club (throughput and conversion, club/membership revenue and churn, DTC, events), and distribution & compliance (three-tier vs self-distribution economics, distributor relationships, TTB / state licensing and excise). Operations and financial decision-support, not legal, tax, or regulatory advice; no licensing/excise determinations and no PII; benchmarks carry a retrieval date + verify-at-use; three-tier / TTB / licensing / excise rules are jurisdiction-specific and flagged for a professional. Ships skills, a decision-tree knowledge bank (Mermaid trees + a dated 2026 reference), best-practices, templates, commands. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Creator-economy business operations team — agents (creator-business-strategist, content-and-audience-manager) for running a creator/media business: the monetization mix (ads, sponsorships, memberships & subscriptions, products/courses, affiliate, services), the platform portfolio (owned vs rented, platform-risk diversification, repurposing), audience funnel & LTV, sponsorship valuation & rate cards, content ops, community & retention, and the creator P&L/MRR. skills (choose-monetization-mix, price-a-brand-deal, plan-content-and-audience-growth), a knowledge bank (a Mermaid monetization-mix tree + a dated 2026 platform/payout/rate reference), best-practices. ADVISORY operations knowledge, not legal/tax/financial advice; payout rules, rate norms, and FTC/ASA disclosure specifics are volatile + jurisdictional, retrieval-dated + verify-at-use; no audience PII. Distinct from marketing-operations, developer-relations, and ecommerce-dtc. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Customer-Success analytics team — specialist agents (cs-analytics-architect, churn-signal-analyst) that own the DOMAIN layer of a CS-health analytics build: the conformed account / health-snapshot / renewal data model, which signals compose the health view, and the transparent rule-based Green/Yellow/Red risk tier (every Red shows why) — no black-box ML in phase one. Domain-neutral: it sits on top of data-platform's pipeline/warehouse/connector layer (which it routes all plumbing to) rather than duplicating it. skills, best-practice rules, a knowledge bank (CS-health/churn signals, renewal lifecycle, NRR/GRR retention metrics, consolidated + risk-tier-escalation Mermaid decision trees), a scenarios bank (field notes), a stdlib cs_calc.py (NRR-GRR + weighted health-score + renewal-risk), and data-model + tier-design templates whose identity spine points at data-platform. Pairs with data-platform; seams to salesforce / tableau / edtech-partner-success. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Customer Support & CX Operations specialist team — agents (support-ops-lead, ticket-deflection-analyst, queue-staffing-specialist, csat-quality-strategist), skills, templates, commands, an advisory hook, best-practice rules, and a research-grounded knowledge bank. A support-ops team for a head of support, CX manager, or founder accountable for cost-to-serve and SLA attainment — it deflects before hiring, staffs to forecast and occupancy, reads CSAT segmented, and treats backlog as arrivals-against-capacity flow. Inherits ravenclaude-core protocols.

by Matt Corbett

Cybersecurity governance, risk & compliance (GRC) team — agents (grc-architect, control-and-evidence-engineer, audit-and-third-party-risk-lead) for the security-compliance program layer: framework selection & scoping (SOC 2 TSC, ISO 27001 + Annex A, NIST CSF 2.0, NIST 800-53), the ISMS, control crosswalk across frameworks, the Statement of Applicability; control implementation & operating effectiveness, policy authoring, evidence collection & continuous control monitoring, Type I vs Type II readiness; audit readiness, gap assessments, and vendor/third-party risk (TPRM tiering, SIG/CAIQ, shared-responsibility, monitoring). Decision-tree bank (Mermaid trees), best-practices, skills, commands, templates, a hook, a grc_calc.py risk/coverage/readiness calculator, scenarios. Seams: AppSec -> security-engineering; financial-regulator -> regulatory-compliance; privacy mechanics -> data-governance-privacy; cloud config -> aws/azure/gcp-cloud. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Data governance & privacy team — agents (data-governance-architect, privacy-compliance-engineer, data-catalog-lineage-engineer) for making data discoverable, trustworthy, and lawfully used: the governance operating model (ownership/stewardship, policies, classification scheme), privacy mechanics (GDPR/CCPA/-style data-subject rights — access/erasure/portability, consent + lawful basis, data minimization, retention, pseudonymization vs anonymization), and a data catalog with lineage + sensitive-data/PII discovery + access governance/DLP. The ENGINEERING of governance, not legal advice. skills, a decision-tree knowledge bank (classification + DSR-handling trees + a dated 2026 map), best-practices, templates, commands, an advisory hook. Seams: financial-regulatory -> regulatory-compliance, warehouse RLS -> data-platform, Purview-in-Fabric -> microsoft-fabric, security verdicts -> security-engineering. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Data-orchestration team — agents (orchestration-architect, pipeline-orchestration-engineer) for the layer that RUNS and SCHEDULES data pipelines: orchestrator selection (Airflow, Dagster, Prefect, Mage, Temporal-for-data; cloud-native MWAA/Step Functions, Azure Data Factory, Cloud Composer/Workflows), DAG and software-defined-asset design, scheduling/triggers (cron, sensor, data-aware), backfills and catchup, idempotency and retries with exponential backoff, partitioning, freshness SLAs and alerting, and lineage. skills (choose-orchestrator, design-dag-and-dependencies, handle-backfills-and-retries), a knowledge bank (a Mermaid selection tree + a 2026 patterns reference), and templates. Distinct from data-platform (ELT/warehouse/BI), analytics-engineering (dbt), and data-streaming-engineering (real-time) — this is the scheduling/run layer they plug into. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Data-platform team — agents (database-setup-guide, etl-pipeline-engineer, dashboard-builder, connector-developer) for cloud DBs, ELT (Airbyte / Fivetran / n8n) with connectors for QuickBooks / Stripe / Salesforce / HubSpot / GA4 / Shopify / HRIS / Planhat / Intercom / Slack-as-source plus 8-vendor support-tool integration coverage (Zendesk, Freshdesk, Intercom Conv+Tkt, SFDC Service Cloud, JSM, HubSpot Service, Help Scout, Front + 2026 Fivetran connector-MAR build-vs-buy math), and embedded dashboards (Evidence.dev / Superset / Metabase / Cube + Tremor). skills (incl. support-ticket-normalization — conformed fct_ticket / fct_conversation_event over 8 vendors; cross-system-identity-resolution — the Salesforce↔Planhat↔Intercom↔Slack account spine), templates, a knowledge bank, best-practices. Opinionated against per-viewer-priced BI for greenfield SMB. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Data-quality & observability team — agents (data-quality-architect, data-quality-engineer) for the layer answering 'is this data CORRECT, FRESH, COMPLETE, and can we TRUST it?': producer-boundary contracts, validation tests (not-null/unique/accepted-values/referential/distribution), freshness/volume/schema-drift/distribution monitors, threshold vs statistical anomaly detection, data-quality SLAs/SLIs, and data-incident response (triage, quarantine/circuit-breaker, root-cause, backfill). Fluent in dbt tests + dbt-expectations, Great Expectations, Soda, Elementary, managed observability (Monte Carlo, Bigeye, Metaplane), and warehouse-native checks. skills, a knowledge bank (tooling decision tree + 2026 patterns reference), and templates. Distinct from data-platform (ELT/warehouse/BI), analytics-engineering (dbt transforms), data-orchestration (schedules the runs), and data-governance-privacy (policy/PII/lineage) — this is the trust/quality layer over all of them. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Exploratory data science & reproducible research team — agents (exploratory-data-scientist, feature-and-modeling-engineer, research-reproducibility-engineer) for the analysis layer between raw data and a defensible result: data profiling/cleaning, EDA, hypothesis generation, communicating findings with uncertainty; feature engineering, classical modeling (regression, trees, boosting), model selection, evaluation (cross-validation, metrics) and leakage avoidance; and the reproducibility spine — notebook hygiene, pinned environments, experiment tracking, data/version control, seeds, and reproducible pipelines. best-practices, decision-tree knowledge bank, skills, commands, templates, a hook, scenarios bank, and stdlib-only ds_calc.py (classification/regression metrics, split-check). Seams: is-the-result-statistically-real -> applied-statistics; productionize/serve/monitor -> ml-engineering; data pipelines/warehouse -> data-platform. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Data-streaming-engineering team — agents (streaming-architect, kafka-pipeline-engineer, stream-processing-engineer) for REAL-TIME data: streaming-vs-batch decision and topology, event streaming + CDC (Kafka/Pulsar/Kinesis, topics/partitioning, schema registry + evolution, the outbox/Debezium CDC pattern), delivery semantics (at-least-once vs exactly-once, idempotency, transactional outbox), and stream processing (Flink/Kafka-Streams: event-time vs processing-time, windowing, watermarks, state, joins, backpressure). skills, a decision-tree knowledge bank (streaming-vs-batch + delivery-semantics trees + a dated 2026 map), best-practices, templates, commands, an advisory hook. Distinct from data-platform (batch ELT) and microsoft-fabric (RTI/Eventstream). Seams: batch ELT -> data-platform, AsyncAPI contracts -> api-engineering, Fabric RTI -> microsoft-fabric, app-side messaging -> backend-engineering. Requires ravenclaude-core@>=0.7.0.

by Matt Corbett

Database-engineering team — agents (schema-architect, query-performance-engineer, migration-engineer, db-reliability-engineer) for the OPERATIONAL/transactional data layer (OLTP): relational schema design and normalization (and when to denormalize), indexing strategy and query/EXPLAIN-plan tuning, safe zero-downtime schema migrations (expand/contract), and connection-pooling, transactions/isolation, replication, and backup/restore reliability. Postgres-leaning, principles portable to MySQL/SQL Server; NoSQL access-pattern guidance where it fits. skills, a decision-tree knowledge bank (index-choice + migration-safety trees + a dated 2026 capability map), best-practices, templates, commands, an advisory hook. Distinct from data-platform (analytics/ELT/warehouse) and analytics-engineering (dbt). Seams: ELT/warehouse -> data-platform, ORM/app data-access -> backend-engineering, managed DB infra -> cloud plugins. Requires ravenclaude-core@>=0.7.0.