power-automate

name	power-automate
description	Veteran-level reference for Power Automate work — expressions, error handling + scopes, child flows, solution-aware flows + connection references, Dataverse triggers, throttling, approvals, performance patterns. Used by `flow-engineer` (primary) and any agent touching flows.

Power Automate Skill

Purpose: Provide veteran-level depth for flow-engineer (and any agent touching flows) on design patterns, troubleshooting, solution-aware best practices, expressions, error handling, performance, and integration with the broader Power Platform ALM story.

When to Use

• Designing or reviewing complex cloud flows (especially solution-aware ones).
• Troubleshooting intermittent failures, throttling, approvals, child flows, or Dataverse trigger issues.
• Needing reference on expressions, run-after configuration, or performance patterns.
• Ensuring flows follow ALM hygiene (connection references, env vars, solution packaging).

How to Use This Skill

1. Read this SKILL.md for the overall playbook and decision framework.
2. Consult specific resources/*.md files on-demand for deep reference (expressions, error handling, etc.).
3. Combine with solution-alm-engineer guidance for packaging, env vars, and pipelines.

Core Playbook

1. Flow Architecture Principles

• Top-level Try-Catch-Finally on every production flow.
• Child flows for any reusable logic used 2+ times.
• Scopes liberally for readability and targeted error handling.
• Prefer solution-aware flows with connection references and environment variables.
• Keep flows lean — refactor large ones into child flows + parent orchestrator.

2. Expression & Dynamic Content Mastery

• Use outputs(), body(), triggerOutputs() correctly.
• Compose early and often for intermediate values (makes debugging easier).
• Master coalesce(), if(), equals(), formatDateTime(), split(), join().
• Avoid hard-coded GUIDs, site URLs, list IDs — move to env vars or parameters.

3. Error Handling & Resilience

• Always configure run after on failure paths.
• Use parallel branches for independent actions + join.
• Implement retry policies thoughtfully (exponential backoff for transient errors).
• For Dataverse triggers: use proper filter expressions and depth control to avoid infinite loops.

4. Performance & Scale

• Increase Apply to each parallelism explicitly (often to 50).
• Use batching / Dataverse Web API for bulk operations instead of sequential loops.
• Watch connector throttling limits (consult resources).
• Consider Logic Apps or Azure Functions for very high-volume or complex orchestration.

5. ALM & Solution Hygiene (Critical for git/ADO)

• Never hard-code connections — always use connection references.
• Use environment variables for everything that changes per environment.
• Test import on a fresh environment.
• Keep flow JSON changes reviewable (small, focused changes preferred).

Recommended Resources (read on demand)

• resources/expressions-and-dynamic-content.md
• resources/error-handling-scopes-child-flows.md
• resources/solution-aware-flows-connection-refs.md
• resources/dataverse-triggers-best-practices.md
• resources/throttling-and-performance.md

This skill expands the knowledge base for the flow-engineer agent and supports the enhanced ALM guidance in solution-alm-engineer.