Builds and deploys a Power Apps code app to Power Platform. Use when deploying changes, redeploying an existing app, or pushing updates.
npx skills add https://github.com/microsoft/power-platform-skills --skill deploy
📋 Shared Instructions: shared-instructions.md - Cross-cutting concerns.
Builds and deploys the app in the current directory to Power Platform.
Check for memory-bank.md in the project root. If found, read it for the project name and environment. If not found, proceed — the project may have been created without the plugin.
npm run build
If the build fails:
Verify dist/ exists with index.html before continuing.
Ask the user: _"Ready to deploy to [environment name]? This will update the live app."_ Wait for explicit confirmation before proceeding.
> Resolve the CLI first (see cli-binary.md): run as $PA app push (npx --no-install pa …), never a bare pa. On power-apps-only projects, translate to power-apps push.
pa app push
Capture the app URL from the output if present.
If deploy fails, report the error and stop — do not retry silently. Common fixes:
pa auth logout (or power-apps logout on power-apps-only projects), then retry — the CLI will re-prompt browser login.environmentId in power.config.json to the correct value and retry.If memory-bank.md exists, update:
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Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
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.
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Take microsoft/power-platform-deploy 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.
The instructions reference npx.
Without those the skill loads but fails at the first command.