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Found 1,548 Skills
Build clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer, RETAIN, GAMENet, SafeDrug, MICRON, StageNet, AdaCare, CNN/RNN/MLP), training with the PyHealth Trainer, computing clinical metrics, and using medical code utilities (ICD/ATC/NDC/RxNorm lookup and cross-mapping). Use this skill whenever the user mentions PyHealth, MIMIC, eICU, OMOP, EHR modeling, clinical prediction, drug recommendation, sleep staging, medical code mapping, ICD/ATC codes, or any healthcare ML pipeline that fits the dataset → task → model → trainer → metrics pattern, even if "PyHealth" isn't named explicitly.
Replace OOTB (out-of-the-box) B2B Commerce components with open source equivalents in site metadata content.json files, or look up the equivalent open code `site:` component for OOTB definitions. Use when users mention "replace OOTB components", "replace commerce components with open code", "swap OOTB for open source", "replace commerce_builder:", "replace OOTB in site", "replace component in site metadata", "replace component definition", "find open code equivalent", "equivalent open code component", "OOTB to open code mapping", "what is the site component for", components "in this view" or "for a given view", or a specific list of component names — and want to update or only discover mappings in their store metadata.
Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files.
Build Celigo B2B Manager EDI integrations -- trading partner onboarding, EDI profiles, file definitions, X12/EDIFACT flow patterns, and transaction monitoring. Use when onboarding partners, editing EDI flows, setting up parsing rules, or monitoring document exchange.
Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).
AWS CloudFormation patterns for ECS clusters, services, and task definitions. Use when creating ECS infrastructure with CloudFormation, configuring container definitions, scaling policies, service discovery, load balancing integration, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and blue/green deployments with CodeDeploy.
This skill provides universal quality standards for any custom task, ad-hoc request, or campaign step that does not have a specific pre-defined instruction set. Apply these standards to deliver world-class marketing assets regardless of task type.
Build a structured taxonomy of failure modes from open-coded trace annotations. Use this skill whenever the user has freeform annotations from reviewing LLM traces and wants to cluster them into a coherent, non-overlapping set of binary failure categories (axial coding). Also use when the user mentions "failure modes", "error taxonomy", "axial coding", "cluster annotations", "categorize errors", "failure analysis", or wants to go from raw observation notes to structured evaluation criteria. This skill covers the full pipeline: grouping open codes, defining failure modes, re-labeling traces, and quantifying error rates.
Defines caching strategies with cache keys, TTL values, invalidation triggers, consistency patterns, and correctness checklist. Provides code examples for Redis, CDN, and application-level caching. Use when implementing "caching", "performance optimization", "cache strategy", or "Redis caching".
Design, apply, and maintain SKOS taxonomies for joelclaw agent workflows. Use when defining concept schemes, classifying agent inputs/outputs, mapping to external vocabularies, or integrating taxonomy metadata with Typesense retrieval.
When the user wants to optimize for Featured Snippets, Position Zero, or snippet extraction. Also use when the user mentions "featured snippet," "position zero," "snippet optimization," "answer box," "definition box," "list snippet," "table snippet," "paragraph snippet," "PAA optimization," or "win position zero."
Conduct structured interviews to gather requirements, clarify specifications, or understand context. This skill should be used when starting a new task that requires understanding user intent, requirements, technical specifications, or context. It supports various interview types including requirements definition, debugging investigation, architecture review, and general information gathering.