DevOps & Infra

microsoft Skill

Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating

microsoft Skill

Monitor robot fleet telemetry via Azure IoT Operations, drift detection, Grafana dashboards, and Fabric analytics

wipcomputer-wip-ai-devops-toolbox Bundle

Complete DevOps toolkit for AI-assisted software development. Release pipeline, license compliance, copyright enforcement, repo visibility guard, identity file protection, manifest reconciler, and best practices. All core tools are agent-callable via MCP.

quick-intel Skill

Design, evaluate, and launch tokens responsibly through Tator. Use when someone has a token idea, wants to launch a coin, needs strategy feedback, or asks about token economics. Covers concept evaluation, launch execution, fee economics, and critical tax/legal implications. Triggers: "token idea", "launch a coin", "review my token", "token strategy", "deploy a token", "coin concept", "is this a good token", "help me launch", "token fees", "creator fees", "token taxes", "launch on base", "launch on solana".

microsoft Bundle

Submit, monitor, analyze, and evaluate LeRobot imitation learning training jobs on OSMO with Azure ML MLflow integration and inference evaluation - Brought to you by microsoft/physical-ai-toolchain

microsoft Skill

Generate, transfer, and consume environment-specific Azure, AKS, OSMO, ACR, and Azure ML deployment bundles. Use when: discovering deployed environment details; creating OSMO image manifests or platform values; preparing a HiL host; uploading or downloading deployment files through Azure Key Vault; or deploying with generated environment configuration.

clickhouse Skill

Set up the `clickhouse-js` repository in a fresh checkout so the agent can run tests, lints, type checks, builds, or examples. Use this skill before invoking any `npm run test:*`, `npm run lint`, `npm run typecheck`, `npm run build`, or `npm run run-examples` script — or after pulling changes that touch any `package.json` (root, `examples/node`, or `examples/web`). Covers Node.js version requirements, installing dependencies across the npm workspaces and the two independent example packages, building the workspace packages so inter-package imports resolve, and starting ClickHouse via Docker Compose for integration tests. Do NOT use this skill for downstream user projects that merely depend on `@clickhouse/client` or `@clickhouse/client-web`; it is specific to contributing to the `ClickHouse/clickhouse-js` repo itself.

wipcomputer-wip-ai-devops-toolbox Bundle

One-command release pipeline. Bumps version, updates changelog + SKILL.md, publishes to npm + GitHub.

wipcomputer-wip-ai-devops-toolbox Bundle

Private-to-public repo sync. Copies everything except ai/ to the public mirror. Creates PR, merges, syncs releases.

jhd3197 Skill

Scaffold a complete extraction pipeline for a new domain — Pydantic model, field definitions, example script, and tests. Use when building a new extraction use case like medical records, invoices, or reviews.

microsoft Bundle

Use when adding, configuring, validating, or troubleshooting OpenTelemetry observability for a Microsoft 365 Agents SDK application in C# / .NET. Trigger when the user mentions OpenTelemetry, OTel, telemetry, traces, metrics, logs, OTLP, Aspire Dashboard, Application Insights, Azure Monitor, distributed tracing, custom ActivitySource or Meter instrumentation, or observing Microsoft.Agents.Core signals.

microsoft Bundle

Use when provisioning Azure resources for a Microsoft Agents SDK application — including creating an Azure Bot Service resource, setting up Entra app registrations, configuring identity credentials (UserManagedIdentity, FederatedCredentials, or ClientSecret), adding a Teams channel, running Bicep deployments for SSO, or setting up OAuth user sign-in connections via az CLI. Trigger even if the user doesn't say "provision" — use on requests like "set up my bot on Azure", "deploy my bot", "configure Azure for my bot", or "get Teams SSO working." Applies to all languages (dotnet, Node.js, Python).

microsoft Bundle

Use when adding, configuring, validating, or troubleshooting OpenTelemetry observability for a Microsoft 365 Agents SDK application in JavaScript or TypeScript. Trigger when the user mentions OpenTelemetry, OTel, telemetry, traces, metrics, logs, OTLP, Aspire Dashboard, Application Insights, Azure Monitor, distributed tracing, custom tracers or meters, or observing @microsoft/agents-telemetry signals.

microsoft Bundle

Use when adding, configuring, validating, or troubleshooting OpenTelemetry observability for a Microsoft 365 Agents SDK application in Python. Trigger when the user mentions OpenTelemetry, OTel, telemetry, traces, metrics, logs, OTLP, Aspire Dashboard, Application Insights, Azure Monitor, distributed tracing, custom tracers or meters, span sampling, or observing microsoft_agents SDK signals.

microsoft Skill

Use when troubleshooting an agent built with the Microsoft Agents SDK (Microsoft.Agents.Hosting.AspNetCore and related packages) in C# / .NET. Trigger on any of these symptoms: build or C# compile errors, crashes on startup, 401 or auth errors on incoming requests, the bot not responding to messages, appsettings.json configuration problems, Azure AD credential failures (AADSTS errors), port conflicts, or the agent not connecting in Teams or the Agents Playground. Use even if the user doesn't mention the SDK by name — trigger on symptoms like "my bot won't start", "getting 401s", or "bot isn't responding."

microsoft Skill

Use when troubleshooting an agent built with the Microsoft Agents SDK (@microsoft/agents-hosting and related packages). Trigger on any of these symptoms: build or TypeScript errors, crashes on startup, 401 or auth errors on incoming requests, the bot not responding to messages, .env configuration problems, Azure AD credential failures (AADSTS errors), port conflicts, or the agent not connecting in Teams or the Agents Playground. Use even if the user doesn't mention the SDK by name — trigger on symptoms like "my bot won't start", "getting 401s", or "bot isn't responding."

sablier-labs Bundle

Write Foundry-based tests and scripts. Trigger phrases - foundry testing, write test, fuzz test, fork test, invariant test, deploy script, gas benchmark, coverage, or when working in tests/ or scripts/ directories.

sablier-labs Bundle

Deploy Sablier protocols to a new EVM chain. Use for deployment preparation, dry runs, broadcasts, resumes, post-deployment checks, or runbooks involving airdrops/, flow/, lockup/, and their Comptroller prerequisite.

grasmash Skill

Connect to an Acquia Source ("Source powered by Drupal CMS") site — its JSON:API and MCP endpoints, OAuth2 auth, the @drupal-canvas CLI, and the Canvas Page API deploy workflow. Use when wiring an AI agent or app to a Source CMS site, building/uploading Drupal Canvas Code Components, deploying landing pages via the Page API, or registering the Source MCP server with Claude Code/Cursor.

grasmash Skill

Reconcile Drupal configuration drift between a working tree and a deployed environment one item at a time, deciding import (disk wins) vs export (DB wins) vs skip for each difference. Use when `drush config:status` shows drift, after pulling a fresh DB, before a deploy, or when local config and a remote/prod environment disagree. Pantheon/Terminus-aware but works with any remote alias; never writes to production.

rivet-dev Skill

Deploy, configure, and integrate Sandbox Agent - a universal API for orchestrating AI coding agents (Claude Code, Codex, OpenCode, Amp) in sandboxed environments. Use when setting up sandbox-agent server locally or in cloud sandboxes (E2B, Daytona, Docker), creating and managing agent sessions via SDK or API, streaming agent events and handling human-in-the-loop interactions, building chat UIs for coding agents, or understanding the universal schema for agent responses.

odewahn Bundle

Interactive modular learning guide for stream processing concepts from DDIA Chapter 11. Use when the user wants to learn about stream processing, messaging systems, event-driven architectures, Kafka, or needs help with the DDIA Chapter 11 curriculum. Provides 15 bite-sized modules (~45 min each) with flexible prerequisites, hands-on AWS Kinesis examples, progress tracking, and Socratic teaching. Topics include streams vs batch, messaging patterns, partitioned logs, databases & streams, and stream processing fundamentals.

phelan164 Bundle

Plan and implement infrastructure, CI/CD, container, deployment, observability, and operational configuration changes with least privilege, staged validation, and rollback awareness. Use for pipelines, infrastructure as code, Kubernetes, containers, release automation, monitoring, and production-readiness work; do not use to perform destructive production actions without explicit authorization.

soundblaster Bundle

Review GitHub pull request CI outcomes with the GitHub CLI and extract actionable failure details from GitHub Actions logs. Use when asked to check failing PR checks, inspect lint/test/type-check errors, identify failing jobs, or summarize why a PR pipeline failed and what to fix first.

ms2sato Skill

Non-obvious operational details of the local dev environments (single-user `dev.sh`, multi-user `dev-multiuser.sh`, Docker dev stack `docker/docker-compose.yml`) — port layout, source-code propagation, sudo boundaries, multi-repo coexistence. Read when a delegated agent or the Orchestrator first needs to interact with the running dev instance, especially for Browser QA, log inspection, or restart workflows.

zenml-io Skill

Scope and decompose ML workflow ideas into realistic ZenML pipeline architectures. Runs an in-depth interview to help users break down ambitious or over-engineered plans into well-composed multi-pipeline setups, identify what belongs in a pipeline vs. what doesn't, define cross-pipeline data flow via the Model Control Plane, and select an MVP to build first. Produces a pipeline_architecture.md specification document. Use this skill whenever a user describes a complex ML workflow, mentions multiple pipelines, talks about end-to-end ML platforms, asks how to structure their ML system in ZenML, or seems to be over-engineering their pipeline design. Also use when the user's pipeline idea sounds like it's trying to do too many things at once, or when they ask about composing pipelines together. Even if the user just says "I want to build an ML pipeline" with a long list of requirements, this skill helps scope it down before the pipeline-authoring skill takes over.

cloudflare Skill

Author Cloudflare Worker Bundler-compatible apps that build and preview correctly inside a space. Use this skill whenever you scaffold, modify, or deploy a project that will be built with `@cloudflare/worker-bundler` (i.e. anything served from `/space/:name/preview/:branch/`). Covers wrangler config, project layout, static asset rules, server entry conventions, npm dependency limits, and the most common cause of blank previews (JSX in browser scripts).

cocoindex-io Bundle

This skill should be used when building data processing pipelines with CocoIndex, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex is Python-native (supports any Python types), has no DSL, and uses version 1.0.0 or later.

theneoai Bundle

Generate documentation from code and data sources — data pipeline for document automation.

theneoai Bundle

Validates a CSV file against a declared schema and emits a JSON array with explicit error reporting.

lando-labs Skill

Deploy, scan, and manage agents and skills. Use for "deploy X", "list agents", "check for updates", "import agents", "find projects", "track project".

zenml-io Bundle

Migrate Argo Workflows, WorkflowTemplates, ClusterWorkflowTemplates, and CronWorkflows to idiomatic ZenML pipelines. Handles concept mapping, YAML-to-Python translation, scheduling, retries, Kubernetes-native pattern analysis, and flags unsupported patterns such as status-based depends logic, shared volumes, containerSet, sidecars, synchronization locks, and Argo Events for human review. Use this skill whenever the user mentions Argo migration, converting Argo YAML, replacing Argo with ZenML, mapping an Argo concept to ZenML, or provides workflow YAML using terms like WorkflowTemplate, CronWorkflow, when, withItems, withParam, containerSet, onExit, Sensor, or EventSource. For quick conceptual questions, answer from the concept map without running the full migration workflow.

zenml-io Bundle

Migrate Flyte workflows, tasks, LaunchPlans, and Flytekit code to idiomatic ZenML pipelines. Handles concept mapping (`@task`->`@step`, `@workflow`->`@pipeline`, `map_task()`->dynamic `.map()`, `conditional()`->dynamic branching, `LaunchPlan`->schedule/config split), code translation, special-type migration (`FlyteFile`, `FlyteDirectory`, `StructuredDataset`, `FlyteSchema`), Docker/image mapping, and flags unsupported patterns (`@eager`, `ContainerTask`, reference entities, checkpointing, interruptible semantics) for human review. Use this skill whenever the user mentions Flyte migration, converting Flyte to ZenML, porting Flyte workflows, replacing Flyte with ZenML, or asks how a Flyte concept maps to ZenML -- even if they do not explicitly say "migrate". Also use when they paste Flytekit code and ask to make it work with ZenML, or when they describe a workflow using Flyte terminology (`@dynamic`, `LaunchPlan`, `map_task`, `conditional`, `ImageSpec`, `FlyteFile`, `StructuredDataset`, `reference_task`, `refer

zenml-io Bundle

Migrate Kedro pipelines and projects to idiomatic ZenML pipelines. Handles concept mapping (node->step, Pipeline->pipeline, Data Catalog->explicit boundary steps plus artifacts, params:->typed parameters), catalog analysis, code translation, hooks/runners/deployment mapping, and flags unsupported patterns (transcoding, dataset lifecycle hooks, namespace remapping, SharedMemoryDataset, slicing semantics) for human review. Use this skill whenever the user mentions Kedro migration, converting a Kedro project to ZenML, porting Kedro pipelines, replacing Kedro orchestration or deployment plugins with ZenML, or asks how a Kedro concept maps to ZenML -- even if they do not explicitly say "migrate". Also use when the user pastes `catalog.yml`, `parameters.yml`, `pipeline_registry.py`, node code, hook code, or describes a workflow using Kedro terminology such as node, pipeline, Data Catalog, `params:`, namespace, modular pipeline, runner, `MemoryDataset`, or transcoding in a ZenML context. If the user just asks a quic

zenml-io Bundle

Migrate Apache Airflow DAGs, operators, and workflows to idiomatic ZenML pipelines. Handles concept mapping (DAG→pipeline, operator→step, XCom→artifact), code translation, scheduling, retry config, Docker settings, and flags unsupported patterns (trigger rules, sensors, dynamic task mapping) for human review. Use this skill whenever the user mentions Airflow migration, converting Airflow DAGs, porting workflows from Airflow, replacing Airflow with ZenML, or asks how an Airflow concept maps to ZenML — even if they don't explicitly say "migrate". Also use when they paste Airflow code and ask to make it work with ZenML, or when they describe a workflow using Airflow terminology (DAG, operator, XCom, sensor, task group) in a ZenML context. If the user just asks a quick conceptual question ("what's the ZenML equivalent of XCom?"), answer it directly from the concept map — no need to run the full migration workflow.

zenml-io Bundle

Migrate Azure Machine Learning SDK v2 pipelines, components, environments, and schedules to idiomatic ZenML pipelines. Handles concept mapping (`@pipeline` -> `@pipeline`, `@command_component` -> `@step`, `Environment(...)` -> `DockerSettings(...)`, AzureML compute -> `AzureMLOrchestratorSettings`), code translation, Azure-aware "keep AzureML" migration paths, and flags unsupported or unsafe patterns (sweep jobs, parallel jobs, managed endpoints, AzureML Registry, Responsible AI dashboard, and unverified control-flow helpers like `if_else` and `do_while`) for human review. Use this skill whenever the user mentions AzureML migration, Azure Machine Learning SDK v2 migration, converting AzureML pipelines or components, porting workflows from AzureML, replacing AzureML authoring with ZenML, or asks how AzureML concepts map to ZenML -- even if they don't explicitly say "migrate". Also use when they paste AzureML SDK v2 code, `mldesigner` components, YAML components, `load_component()` usage, MLTable/data asset def