team-building
Design and create AI team packages — manifest format, member structure, directory layout
Design and create AI team packages — manifest format, member structure, directory layout
Expert guidance for Nixpacks, the build system created by Railway that automatically detects your application's language and framework, installs dependencies, and produces optimized Docker images — all without writing a Dockerfile. Helps developers configure Nixpacks for custom build steps, multi-language projects, and CI/CD integration.
Build, review, debug, and stabilize Spack-based HPC software stacks. Use when working with Spack specs, variants, compilers, externals, environments, concretization, compiler or MPI matrices, site stacks, binary reuse, or Spack install and reuse failures.
Show migration progress by comparing legacy quotevote-monorepo against current quotevote-next implementation
Setting up a Capsem development environment from scratch. Use when onboarding a new developer, setting up a new machine, or troubleshooting environment issues. Covers prerequisites, first-time setup, tool installation, VM asset builds, container runtime configuration (Colima/Docker memory and CPU requirements), and verification steps.
Manages Kubernetes clusters and Helm charts. Use when the user wants to write Kubernetes manifests, create Helm charts, deploy applications, debug pods, configure networking (services, ingress), set up autoscaling, manage secrets and config maps, write operators, troubleshoot cluster issues, or implement GitOps workflows. Trigger words: kubernetes, k8s, kubectl, helm, helm chart, pod, deployment, service, ingress, namespace, configmap, secret, hpa, pvc, statefulset, daemonset, cronjob, operator, kustomize, argocd, flux, gitops, node pool, taint, toleration, affinity.
Deploy web applications to any server with Kamal — zero-downtime Docker deployments without Kubernetes. Use when someone asks to "deploy to a VPS", "deploy without Kubernetes", "Kamal deploy", "simple Docker deployment", "deploy Rails/Node/Python to a server", "zero-downtime deployment to bare metal", or "replace Heroku with a VPS". Covers Docker-based deployment, zero downtime with Traefik, multi-server, secrets, and accessory services.
Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.
Deploy and configure Thanos for long-term Prometheus metric storage, global querying across multiple Prometheus instances, and data compaction. Use when a user needs durable metric storage in object storage, a unified query view across clusters, downsampling for historical data, or high-availability Prometheus with deduplication.
Configure Prometheus Alertmanager for alert routing, grouping, silencing, and notification delivery. Use when a user needs to set up alert receivers (Slack, PagerDuty, email), define routing trees, manage silences and inhibition rules, or troubleshoot alert delivery pipelines.
You are an expert in Traceloop and its OpenLLMetry SDK, the open-source observability framework that extends OpenTelemetry for LLM applications. You help developers instrument AI pipelines with automatic tracing for OpenAI, Anthropic, Cohere, LangChain, LlamaIndex, vector databases, and frameworks — exporting to any OpenTelemetry-compatible backend (Grafana Tempo, Jaeger, Datadog, Honeycomb, Traceloop Cloud).
You are an expert in Langtrace, the open-source observability platform for LLM applications built on OpenTelemetry. You help developers trace LLM calls, RAG pipelines, agent tool use, and chain executions with automatic instrumentation for OpenAI, Anthropic, LangChain, LlamaIndex, and 20+ providers — providing cost tracking, latency analysis, token usage, and quality evaluation in a self-hostable dashboard.
Death & Sourdough series continuity checker. MANDATORY before writing or editing ANY prose chapter for the Death & Sourdough project. Ensures cross-referencing of established facts (character details, locations, timeline, objects, quoted text, relationship dynamics) against the Continuity Bible, and updates the bible after writing. Trigger whenever: (1) writing a new chapter, (2) revising or fleshing out an existing chapter, (3) adding new characters, locations, or named details to the prose.
Self-improvement system for managing (finding/using, saving/adding, and pruning) solutions, patterns, lessons learned, and workarounds. Use this skill whenever a mode says "check learnings", "check memories", "prior solutions", "remember this", "save this pattern", or when you discover a non-obvious fix after 2+ failed attempts. Also trigger when encountering unexpected behavior that others might hit.
Expert guidance for ClearML, the open-source MLOps platform for experiment tracking, pipeline orchestration, data management, and model deployment. Helps developers set up ML experiment tracking with minimal code, build reproducible pipelines, and manage the full ML lifecycle from training to serving.
Parse, navigate, and query materials science ontology structures — browse class hierarchies, inspect individual classes and their properties, look up object and data property definitions with domain/range, search for ontology terms by keyword, and parse or summarize raw OWL/XML files. Supports the OCDO ecosystem (CMSO, ASMO, CDCO, PODO, PLDO, LDO). Use when exploring what classes or properties an ontology provides, finding the right CMSO term for a crystal structure or simulation concept, understanding parent-child class relationships, or onboarding to an unfamiliar materials ontology, even if the user only says "what ontology terms describe my FCC copper simulation" or "show me the CMSO class hierarchy."
Build, review, debug, and automate GROMACS molecular simulation workflows. Use when working with GROMACS preprocessing, topology and coordinate files, `.mdp` parameters, energy minimization, equilibration, production MD, analysis commands, or GROMACS runtime errors.
Generate, review, debug, and recover LAMMPS molecular dynamics input scripts. Use when working with LAMMPS command ordering, data files, force fields, ensembles, neighbor settings, thermo output, or common runtime errors such as lost atoms and non-numeric pressure.
Build, review, debug, and automate ElmerFEM workflows. Use when working with Elmer `.sif` solver input files, mesh directories, equation and material blocks, multiphysics coupling, boundary conditions, transient controls, or ElmerSolver execution and output issues.