> browse/registry

> axiom-swiftdata-migration-diag

Use when SwiftData migrations crash, fail to preserve relationships, lose data, or work in simulator but fail on device - systematic diagnostics for schema version mismatches, relationship errors, and migration testing gaps

> axiom-swiftdata-migration

Use when creating SwiftData custom schema migrations with VersionedSchema and SchemaMigrationPlan - property type changes, relationship preservation (one-to-many, many-to-many), the willMigrate/didMigrate limitation, two-stage migration patterns, and testing migrations on real devices

> axiom-testflight-triage

Use when ANY beta tester reports a crash, ANY crash appears in Organizer or App Store Connect, crash logs need symbolication, app was killed without crash report, or you need to triage TestFlight feedback

> axiom-testing-async

Use when testing async code with Swift Testing. Covers confirmation for callbacks, @MainActor tests, async/await patterns, timeout control, XCTest migration, parallel test execution.

> axiom-ui-testing

Use when writing UI tests, recording interactions, tests have race conditions, timing dependencies, inconsistent pass/fail behavior, or XCTest UI tests are flaky - covers Recording UI Automation (WWDC 2025), condition-based waiting, network conditioning, multi-factor testing, crash debugging, and accessibility-first testing patterns

> axiom-ui-recording

Use when setting up UI test recording in Xcode 26, enhancing recorded tests for stability, or configuring test plans for multi-configuration replay. Based on WWDC 2025-344 "Record, replay, and review".

> inspired-product

Build empowered product teams using discovery and delivery dual-track. Use when the user mentions "product discovery", "empowered teams", "feature factory", "product roadmap", "opportunity assessment", or "product vision". Covers product discovery techniques, team structure, and continuous value delivery. For customer interviews, see mom-test. For ongoing discovery systems, see continuous-discovery.

> lean-startup

Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", or "test assumptions". Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done.

> refactoring-patterns

Apply named refactoring transformations to improve code structure without changing behavior. Use when the user mentions "refactor this", "code smells", "extract method", "replace conditional", or "technical debt". Covers smell-driven refactoring, safe transformation sequences, and testing guards. For code quality foundations, see clean-code. For managing complexity, see software-design-philosophy.

> elixir-antipatterns

Core catalog of 8 critical Elixir/Phoenix anti-patterns covering error handling, separation of concerns, Ecto queries, and testing. Trigger: During Elixir code review, refactoring sessions, or when writing Phoenix/Ecto code.

> playwright

Playwright E2E testing patterns. Trigger: When writing E2E tests - Page Objects, selectors, MCP workflow.

> pytest

Pytest testing patterns for Python. Trigger: When writing Python tests - fixtures, mocking, markers.

> quality-engineering-jira-integration

Standards for retrieving Jira issue details and linking Zephyr test cases back to Jira. Use when retrieving Jira issues or linking Zephyr test cases to Jira tickets. (triggers: **/jira_*.xml, **/test_case.json, jira issue, link zephyr, jira details, jira mcp)

> mom-test

Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but don't buy", "leading questions", or "The Mom Test". Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.

> electron

Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron applica

> code-review

Perform code reviews following Sentry engineering practices. Use when reviewing pull requests, examining code changes, or providing feedback on code quality. Covers security, performance, testing, and design review.

> swift-testing-expert

Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.

> pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

> azure-app-testing

Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure App Testing applications. Not for Azure Test Plans (use azure-test-plans), Playwright Workspaces (use azure-playwright-workspaces), Azure DevOps (use azure-devops), Azure App Service (use azure-app-service).

> scientific-brainstorming

Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.