DevOps & Infra

zenml-io Bundle

Migrate Dagster assets, ops, graphs, jobs, and software-defined asset workflows to idiomatic ZenML pipelines. Handles concept mapping (asset->step output, job->pipeline, IOManager->artifact store/materializer + explicit IO steps), asset-boundary planning, code translation, scheduling, retry config, resources/config migration, and flags unsupported patterns (asset selection, partitions/backfills, sensors, declarative automation, freshness policies, observable source assets) for human review. Use this skill whenever the user mentions Dagster migration, converting Dagster assets or jobs, porting workflows from Dagster, replacing Dagster with ZenML, or asks how a Dagster concept maps to ZenML -- even if they do not explicitly say "migrate". Also use when they paste Dagster code and ask to make it work with ZenML, or when they describe a workflow using Dagster terminology (`@asset`, `@multi_asset`, `Definitions`, `IOManager`, `ConfigurableResource`, partitions, sensors, asset checks) in a ZenML context. If the use

zenml-io Bundle

Migrate Prefect flows, tasks, and deployment patterns to idiomatic ZenML pipelines. Handles concept mapping (`@flow`→`@pipeline`, `@task`→`@step`, result persistence→artifacts), dynamic-execution analysis, code translation, scheduling, retries, Blocks/secrets decomposition, and flags unsupported patterns (`allow_failure()`, `return_state=True`, pause/suspend, global concurrency, task-runner semantics) for human review. Use this skill whenever the user mentions Prefect migration, converting Prefect flows, porting workflows from Prefect, replacing Prefect with ZenML, or asks how a Prefect concept maps to ZenML — even if they do not explicitly say "migrate". Also use when they paste Prefect code and ask to make it work with ZenML, or when they describe a workflow using Prefect terminology (`@flow`, `@task`, `.submit()`, `.map()`, `State`, Blocks, Deployments, work pools, Automations) in a ZenML context. If the user asks a quick conceptual question ("what is the ZenML equivalent of a Prefect Block?"), answer it d

zenml-io Bundle

Migrate Metaflow flows and Outerbounds-flavored Metaflow projects to idiomatic ZenML pipelines. Handles concept mapping (FlowSpec->pipeline, @step->@step, self.* artifacts->explicit returns and inputs), code translation for Parameters, IncludeFile, Config, self.next transitions, branch/join, foreach, scheduling, retry/resource/dependency decorators, and flags unsupported or high-risk patterns (@catch, merge_artifacts, resume and checkpoint semantics, recursion, event triggers, @batch) for human review. Use this skill whenever the user mentions Metaflow migration, converting FlowSpec code, porting flows from Metaflow or Outerbounds, replacing Metaflow orchestration with ZenML, or asks how a Metaflow concept maps to ZenML -- even if they don't explicitly say "migrate". Also use when they paste FlowSpec code or describe workflows using Metaflow terminology (self.next, foreach, current, Parameter, IncludeFile, Config, @catch, @kubernetes, @batch, Runner, Deployer) in a ZenML context. If the user just asks a quick

zenml-io Bundle

Author ZenML pipelines: @step/@pipeline decorators, type hints, multi-output steps, dynamic vs static pipelines, artifact data flow, ExternalArtifact, YAML configuration, DockerSettings and ResourceSettings for remote execution, custom materializers, metadata logging, secrets management, pipeline deployments, live streaming events, lifecycle hooks, and custom visualizations. Use this skill whenever asked to write a ZenML pipeline, create ZenML steps, make a pipeline work on Kubernetes/Vertex/SageMaker, add Docker settings, write a materializer, create a custom visualization, handle "works locally but fails on cloud" issues, or configure pipeline YAML files. Even if the user doesn't explicitly mention "pipeline authoring", use this skill when they ask to build an ML workflow, data pipeline, or training pipeline with ZenML.

zenml-io Bundle

Migrate Amazon SageMaker Pipelines and workflow code to idiomatic ZenML pipelines. Handles concept mapping (Pipeline->@pipeline, ProcessingStep/TrainingStep->@step, PropertyFile/JsonGet->artifacts), code translation, SagemakerOrchestratorSettings mapping, scheduling, model-registration strategy, and flags unsupported or high-risk patterns (CallbackStep, LambdaStep handshake semantics, step.properties placeholders, dynamic-pipeline scheduling on SageMaker) for human review. Use this skill whenever the user mentions SageMaker migration, converting SageMaker Pipelines, porting workflow code from SageMaker, replacing SageMaker DSL authoring with ZenML, or asks how a SageMaker Pipelines concept maps to ZenML -- even if they do not explicitly say "migrate". Also use when they paste `sagemaker.workflow.*` code and ask to make it work with ZenML, or when they describe a workflow using SageMaker terms (`ProcessingStep`, `TrainingStep`, `ConditionStep`, `PropertyFile`, `JsonGet`, `ModelStep`, `PipelineSession`) in a Ze

zenml-io Bundle

Migrate Databricks Workflows (Lakeflow Jobs) to idiomatic ZenML pipelines. Handles concept mapping (Job->pipeline, Task->step, task values->artifact), notebook refactoring, code translation for all Databricks task types (notebook_task, python_wheel_task, sql_task, dbt_task, condition_task, for_each_task, run_job_task, spark_jar_task), scheduling, retry config, compute mapping, and flags unsupported patterns (file arrival triggers, run_if semantics, shared cluster state, DBFS paths) for human review. Use this skill whenever the user mentions Databricks migration, converting Databricks Jobs or Workflows, porting workflows from Databricks, replacing Databricks orchestration with ZenML, or asks how a Databricks concept maps to ZenML -- even if they don't explicitly say "migrate". Also use when they paste Databricks job JSON or notebook code and ask to make it work with ZenML, or when they describe a workflow using Databricks terminology (task, job, notebook_task, dbutils, task values, job clusters, condition_task

briansunter Skill

Use when building, testing, typechecking, or publishing the Pokemon Pocket MCP server package. Activates when user mentions build, publish, release, typecheck, npm publish, or CI/CD. Provides build commands, type checking, test running, and semantic release workflow.

vincenthopf Skill

Full bug-fix pipeline from root cause analysis through implementation. Separates investigation, proposal, alignment, and execution into distinct agent responsibilities. Also applies to features and refactors by skipping root cause analysis and starting at proposal.

vllm-project-vllm-omni Bundle

Add a new diffusion model (text-to-image, text-to-video, image-to-video, text-to-audio, image editing) to vLLM-Omni, including native non-Diffusers ports, reference-parity validation, Cache-DiT, offload, and parallelism support (TP, SP/USP, CFG-Parallel, HSDP). Use when integrating or reviewing a new diffusion model, porting a Diffusers pipeline or custom model repository, creating a DiT adapter, reusing shared examples, or qualifying multi-GPU and memory optimizations.

zenstory-ai Bundle

Turn a novel into a fully playable game on the selected target platform. Orchestrates the whole adaptation pipeline — requirements intake, gameable deconstruction, concept selection, world and visual design, target-runtime build, and evidence-based QA — for a novel in any language. Use for novel to game, story to game, book to game, adapt this novel into a game, turn this book into a playable prototype, make an interactive story or text adventure from this novel. NovelToGame 总入口。把任意语言的原始小说、拆文库或 oh-story 写作工程转成有原著依据、可在目标平台完整游玩的游戏，编排游戏化拆解、概念选择、游戏与视觉设计、目标运行环境构建和证据化质量验证。用于小说转游戏、把这本书做成游戏、把小说改成互动小说 / 互动叙事 / 文字冒险游戏等需求。

thu-team-eureka Skill

Interactively generate all required EUREKA problem input files (INSTRUCTION.md, SUBMISSION_FORMAT.md, evaluate.py) and the launch script (run.sh) from a researcher's natural language description, then validate the evaluation pipeline.

thu-team-eureka Skill

Validate problem setup, test the evaluation pipeline, and configure the environment before the propose-implement loop begins.

abdullah1854 Skill

Infrastructure deployment for VPS, Docker, and cloud platforms. Activates for "deploy", "setup server", "docker", "coolify", "VPS", "SSH", "nginx", "production", "hosting" requests.

ragnarok22 Bundle

Audit Django codebases for security, performance, correctness, and architecture antipatterns. Run system checks, migration drift checks, and static rule scans, then output a 0-100 health score with actionable fixes. Use when users ask to scan a Django backend, run a Django health check, review backend code quality, or perform a pre-deploy audit.

ragnarok22 Bundle

Verify Dockerfiles and Docker Compose manifests for security issues, reliability risks, optimization opportunities, syntax errors, and misconfiguration before builds or deploys. Run deterministic checks (`scripts/verify-docker.sh`, `docker compose config -q`, optional `hadolint`) and produce a 0-100 health score with prioritized fixes. Use when users ask to validate Dockerfile(s), docker-compose/compose YAML files, harden container configuration, optimize image/runtime setup, debug configuration failures, or run a pre-deploy Docker audit.

ghostscientist Bundle

Use this skill when deploying a machine learning model to a Hugging Face Space, creating an interactive ML demo, or publishing a model with a web UI. Covers Gradio and Streamlit apps, chat and image-generation interfaces, LoRA/PEFT adapters, ZeroGPU and paid GPU hardware, and managing existing Spaces. Use it whenever the user mentions Hugging Face Spaces, wants to "put a model online", "make a demo for my model", "share my fine-tune", or deploy a model they just trained — even if they don't say "Space" or "Gradio" explicitly.

abdullah1854 Skill

Hostinger-specific deployment protocol handling OPcache, CDN caching, and hPanel Git mechanism. Activates for "deploy to hostinger", "hostinger", "redeploy", "publish website", "push to production" when target is Hostinger.

obeone Bundle

Generate production-ready Helm charts on the bjw-s-labs common library (app-template v5, v4 legacy). Use for new charts, Compose-to-Helm conversion, sidecars, init containers, services, ingress, persistence, StatefulSets, HPAs, Service/PodMonitors, and NetworkPolicies.

obeone Bundle

Create and optimize Dockerfiles and Compose files with BuildKit, multi-stage builds, cache mounts, and non-root hardening. Also triggers on container images, build performance, or Docker security, even without the word 'Dockerfile'.

miles990 Skill

Deploy Kuro changes through CI/CD pipeline with pre-flight checks and post-deploy verification

microsoft Skill

Enable tracing and logging for Microsoft Agent Framework (MAF) workflows. Configures OpenTelemetry export to Azure Application Insights and/or a generic OTLP endpoint using environment variables. Adds required packages to requirements.txt. WHEN: enable tracing, add tracing, enable logging, add logging, configure telemetry, Application Insights for MAF, OTLP export, observe workflow, monitor agent workflow, trace agent framework, instrument MAF, add observability, trace workflow executions, debug workflow.

microsoft Bundle

Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project. Wraps any workflow into an init()/run() scoring script, creates conda environment, endpoint and deployment YAMLs, deploy script, and assigns RBAC. Supports managed identity auth and Application Insights tracing. WHEN: deploy MAF workflow, deploy agent-framework workflow, create online endpoint for MAF, deploy workflow to AML, deploy workflow to Foundry project, managed online endpoint for agent workflow, wrap workflow in scoring script, deploy agent as endpoint, realtime endpoint in Foundry project.

radixark Bundle

Prepare a new physical CI host so /data/miles_ci is canonical — a real directory on the biggest disk, or a symlink to it — before installing miles GitHub Actions runners. Triggers, "setup ci host", "/data/miles_ci not ready", "miles ci host bootstrap", or similar. Idempotent; safe to re-run. Run once per host before either the README's docker-compose runner flow or `manage-gh-runners`. Boundary vs `manage-gh-runners`, this skill only prepares the host filesystem layout (big-disk detection, mkdir, symlink); it does NOT add, remove, or talk to GitHub runners.

radixark Bundle

Add, remove, list, or swap GitHub Actions self-hosted runners on a CI host that uses the env-var-driven `gh-runner` docker image (raw `docker run`, no compose). Triggers, "add gh runner", "remove gh runner", "list ci runners", or similar. Run `setup-ci-host` first if /data/miles_ci is not yet provisioned. Boundary vs the `actions-runner` + docker-compose flow documented in `tests/ci/README.md`, only use this skill when `docker ps` shows the `gh-runner` image. Does NOT prepare the host filesystem layout — that is `setup-ci-host`'s job.

ukgovernmentbeis Skill

Run the gated test classes that plain `pytest` skips (slow Docker/sandbox tests, live model-provider API tests, flaky tests, trio variants). Use when asked to run slow, live, api, or trio tests, when debugging one, or when a change touches model providers, sandbox or tool code, agents, or async plumbing and needs its gated coverage run.

way-platform Bundle

Write, review, and refactor Terraform HCL for GCP. Use when editing .tf files, managing IAM, writing terraform tests, or organizing GCP Terraform modules.

way-platform Bundle

Spacelift for Terraform GitOps. Use when working with Spacelift stacks, runs, policies, contexts, worker pools, drift detection, or spacectl CLI.

way-platform Bundle

Apache Beam (Python SDK) and Google Cloud Dataflow. Use when creating, debugging, or reviewing Python data pipelines — batch/streaming, Protobuf, Flex Templates, windowing, stateful processing.

dotnet Bundle

**WORKFLOW SKILL** - First-run flow for adding Aspire to a repo. Picks `aspire new` (greenfield) or `aspire init` (existing repo), drops the AppHost skeleton, then hands off to `aspireify` for resource wiring. USE FOR: aspire init, aspire new, aspire-starter, aspire-ts-starter, aspire-py-starter, add Aspire to existing repo, scaffold Aspire app, bootstrap Aspire, no AppHost detected, install aspireify, generated .aspire/modules. DO NOT USE FOR: AppHost wiring on an existing AppHost (use aspireify), start/stop/wait (use aspire-orchestration), deploy/publish (use aspire-deployment), logs/traces (use aspire-monitoring), repo that already has an AppHost. INVOKES: aspire CLI (init, new, doctor), aspireify (handoff after skeleton drop). FOR SINGLE OPERATIONS: Run `aspire init` or `aspire new TEMPLATE` directly.

dotnet Bundle

**WORKFLOW SKILL** — Deploy Aspire apps from AppHost models to Docker Compose, Kubernetes, Azure, or AWS. WHEN: "deploy Aspire app", "publish Aspire artifacts", "deploy to Azure Container Apps", "generate Kubernetes artifacts", "tear down Aspire deployment". INVOKES: aspire CLI, Aspire docs, target cloud/container CLIs. FOR SINGLE OPERATIONS: use generic Azure, Kubernetes, Docker, or AWS tools only when no Aspire AppHost exists.

dotnet Bundle

**ANALYSIS SKILL** - Observe Aspire apps: logs, traces, metrics, resource state, telemetry export, browser telemetry, and the standalone dashboard. Routes between local Aspire CLI, AKS workload diagnostics, and deployed Azure resource health. USE FOR: aspire logs, aspire otel logs, aspire otel traces, aspire otel spans, aspire describe, aspire ps, aspire export, aspire dashboard run, --include-hidden, browser logs in dashboard, WithBrowserLogs, App Insights query, AKS pod logs, container app logs. DO NOT USE FOR: start/stop/wait (use aspire-orchestration), deploy/publish/destroy (use aspire-deployment), AppHost code edits like WithBrowserLogs() (use aspireify), Azure provisioning (use azure-prepare). INVOKES: aspire CLI, azure-diagnostics (deployed Azure), kubectl + Container Insights. FOR SINGLE OPERATIONS: Run the aspire CLI command directly for quick log or describe lookups.

mit17k Skill

Production-ready patterns for Claude Code hooks and automation. Use when implementing security hooks, auto-formatting, CI/CD integration, audit logging, or notification systems.

seeed-studio Bundle

Expert guide for CV181X/CV182X/CV180X (SG200X) multimedia development using CVI MPI API. Use this skill when working with: VI (video input/camera/ISP), VPSS (video processing/scaling/crop), VENC (H.264/H.265/JPEG encoding), VDEC (decoding), VB (video buffer pools), SYS binding, or any CVI_* API calls. Covers camera pipeline setup, offline VPSS processing, VB pool planning, and error diagnosis (ERR_VPSS_NOBUF, ERR_VB_NOBUF). API details in references/.

seeed-studio Bundle

Expert guide for converting ONNX models to CVIMODEL format for Sophgo CV181x TPU. Supports YOLO11/YOLO26 (detect, pose, seg, cls), BiSeNetv2 (semantic segmentation), and PP-LiteSeg (semantic segmentation). Includes tested conversion scripts, quantization tables (qtables), ION memory optimization (--quant_output), validation workflow, and complete documentation. Use when user needs to convert ONNX models to CVIMODEL, set up TPU-MLIR conversion pipeline, configure output names and quantization, optimize ION memory usage, validate conversion accuracy, or troubleshoot conversion issues.

kodustech Skill

Use when the user wants to validate the Kodus SSO flow end-to-end (cookie-domain regression for self-hosted, Bug 1 force-dynamic, SAML round-trip via Keycloak), confirm the SSO test still passes after changes, or regression-check before merging code that touches `auth.controller.ts`, `derive-sso-cookie-domain.ts`, `apps/web/src/app/(auth)/sso-callback/page.tsx`, or `libs/ee/sso/`. Also triggers on phrases like "test SSO", "validate SSO", "SSO regression", "rodar teste de SSO", "verificar SSO", "SSO selfhosted vs cloud".

alexander-danilenko Skill

Apply these opinionated .NET 8 architecture conventions whenever structuring or reviewing a backend service: clean architecture layering and which direction dependencies point, when CQRS with MediatR is worth it, cross-cutting concerns as pipeline behaviours, minimal APIs grouped by feature, keeping DbContext in Infrastructure, health checks and structured logging, WebApplicationFactory integration tests, and when AOT pays off.