Track which stacks across a Pulumi organization use a specific package and at what versions. Use for cross-stack audits, identifying outdated or unmaintained package versions across many stacks, finding affected stacks before publishing breaking changes to a component package, or planning coordinated upgrade rollouts. Do NOT use for upgrading a cloud provider package (pulumi-aws, pulumi-azure-native, pulumi-gcp, pulumi-kubernetes, etc.) in a single project — use skill `provider-upgrade` instead. Do NOT use for general infrastructure creation, resource provisioning, or how-to questions about a package.
npx skills add https://github.com/pulumi/agent-skills --skill package-usage
Query the Pulumi Cloud API with the pulumi api CLI subcommand. It authenticates with your existing Pulumi credentials and returns JSON.
pulumi api /api/registry/packages -F name={package_name} -F orgLogin={orgName}
Include orgLogin with the user's organization name. Omit -F name=... to list all packages visible to the organization (useful when the user has not named a specific package). The response contains a packages array. Each entry has a version field (the latest version), plus name, publisher, source, and packageStatus.
pulumi api /api/orgs/{orgName}/packages/usage -F packageName={package_name}
Replace {orgName} with the org name from context, PULUMI_ORG, or ask the user. packageName is required; query one package at a time.
Response fields:
packageName: The queried packagestacks: Array of {stackName, projectName, version, lastUpdate}totalStacks: Total countUse when the user wants to know which stacks are using an outdated version of a package.
version against the latest to identify outdated stacksPresent results as a markdown table followed by a summary line:
| Project | Stack | Current Version | Latest Version | Status |
|---------|-------|-----------------|----------------|--------|
| my-app | dev | 6.40.0 | 6.52.0 | Outdated |
| my-app | prod | 6.52.0 | 6.52.0 | Up-to-date |
2 of 2 stacks checked. 1 outdated.
This skill identifies outdated stacks. It does not perform the upgrade itself. For actually bumping a package version in a project — editing package.json, requirements.txt, pyproject.toml, go.mod, or Pulumi.yaml, running pulumi preview, and reconciling the diff — hand off to the provider-upgrade skill.
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take pulumi/package-usage from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.