Invalid-Name
This skill has an uppercase letter in the name which should fail validation.
missing-references
This skill references rules that do not have corresponding files in the references directory.
too-long-skill
This skill has more than 500 lines which should fail validation.
valid-skill
A valid test skill with proper formatting. This skill should pass all validations and serves as a reference for the expected format.
app-design-architect
Design screens and navigation using Apple HIG patterns and components
app-design-discover
Define app goals and prioritize features for iOS/iPadOS/macOS
app-design-refactor
Redesign an app whose goals/features are solid but design layer needs rework
app-design-validate
Validate App design specs against actual Swift/SwiftUI code to find compliance gaps
app-design
Full App design workflow — check progress and continue from where you left off
apple-hig
This skill should be used when designing UI for Apple platforms (iOS, iPadOS, macOS, tvOS, visionOS, watchOS). Covers choosing the right component (tab bar vs sidebar, sheet vs popover, list vs collection), applying HIG patterns (onboarding, search, settings, data entry, modality), and making visual design decisions (typography, color, layout, dark mode, motion). Activates on questions like "which navigation pattern should I use," "how should I design this screen for iPad," "what does Apple recommend for onboarding," or "check this design against HIG."
apple-engineering
End-to-end iOS/iPadOS engineering workflows grounded in Apple documentation: data modeling and persistence strategy (SwiftData/Core Data), performance optimization (Apple's 8 metrics, Instruments, MetricKit), debugging (crash/hang/memory/threading/data corruption), and refactoring existing model decisions. Reads design/ artifacts from app-design when available for richer, design-informed engineering. Use when users ask to design or revise iOS data architecture, choose persistence, profile and optimize performance, create monitoring/performance tests, diagnose app issues, or resume a structured engineering workflow that writes artifacts under engineering/.
ios-debugger-agent
Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.
swiftui-liquid-glass
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
swiftui-performance-audit
Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
swiftui-ui-patterns
Best practices and example-driven guidance for building SwiftUI views and components, including navigation hierarchies, custom view modifiers, and responsive layouts with stacks and grids. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens with VStack/HStack, managing @State or @Binding, building declarative iOS interfaces, or needing component-specific patterns and examples.
swiftui-view-refactor
Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.
dev-debug-cpp
C++ debugging for segfaults, memory corruption, threading issues, and linker/ABI problems. Use when encountering crashes (exit code 139/SIGSEGV), memory leaks, data races, undefined behavior, or when debugging native Node.js addons, FFmpeg integrations, or any C++ code that crashes mysteriously.
python-performance
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python-project
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python-testing
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Google Shell Style Guide
This skill should be used when the user asks to "refactor shell script", "fix bash style", "review shell code", "apply Google style guide", "improve shell script", mentions "shellcheck", or discusses bash/shell coding standards and best practices.
bootstrap-context
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build-golden-set
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build-observability
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diagnose
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expand-personalisation
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explore-events
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marketplace-personalisation
Use this skill whenever designing, building, debugging, reviewing, or improving a personalisation or recommendation system for a two-sided trust marketplace built on AWS Personalize — covers event tracking, dataset and schema design, two-sided matching, cold start, feedback loops, bias control, recipe selection, serving-time re-ranking, observability, and a diagnostic playbook for existing systems. Trigger even when the user does not explicitly mention "AWS Personalize" but is working on recommendations, ranking, search, homepage personalisation, or anything that matches seekers and providers across a trust-based catalog.
simple-git-worktrees
This skill should be used when the user asks to "create worktree", "remove worktree", "work in worktree", "switch to worktree", "clean up worktree", mentions "repo--branch pattern", or during plan execution when worktree isolation is needed. Documents the sibling directory worktree pattern for simple, safe git worktree workflows.
marketplace-pre-member-personalisation
Use this skill whenever designing, building, reviewing, or diagnosing the pre-member journey of a two-sided trust marketplace — from anonymous landing through onboarding, registration, and the paid-membership paywall. Covers anonymous signal inference, what pet owners specifically need to validate before paying (safety, availability, competence, effort, local cost comparison), what pet sitters specifically need to validate (opportunity, first-stay path, daily commitment, hidden costs), information-asymmetry closure, progressive profile building, social proof, conversion psychology, onboarding intent capture, identity stitching, and pre-member measurement. Every rule is grounded in published consumer-trust and decision research — Cialdini, Kahneman, Roth, Fogg, Bandura, Slovic, Nielsen Norman Group, and the Airbnb / DoorDash engineering literature. Triggers on tasks involving visitor-to-member conversion, anonymous personalisation, onboarding flow design, paywall timing, pre-member ranking, or any question about what a pet owner or pet sitter needs to see before paying. Use this skill BEFORE marketplace-personalisation and marketplace-search-recsys-planning — it covers everything that happens before the paid-member boundary.
marketplace-recsys-feature-engineering
Use this skill whenever deciding what features to extract from raw marketplace assets — listing photos, owner-entered listing metadata, sitter wizard responses — to power item-to-item (similar listings), user-to-item (homefeed ranking), or user-to-user (mutual-fit matching) recommenders in a two-sided trust marketplace. Covers asset auditing, first-principles feature decomposition from the decision the user is making, vision-feature extraction (CLIP, room-type classification, amenity detection, aesthetic and quality scoring), listing text and metadata encoding (categoricals, multi-hot amenities, H3 geo-hashing, sentence-transformer description embeddings, structured pet triples), sitter wizard design (information-gain ordering, multiple-choice over free text, genuine skippability, hard constraint versus soft preference), derived-composition patterns for i2i / u2i / u2u (precomputed ANN shelves, multi-modal fusion, two-tower affinity, symmetric mutual-fit scoring, interpretable subscores), feature quality governance (single registry, training-serving parity, coverage and drift alarms, PII scrubbing, schema versioning), and incremental value proof (one feature at a time, ablation A/B, kill reviews, exploration slice, permanent feature-free baseline). Trigger even when the user does not explicitly say "feature engineering" but is asking how to get more signal out of listing photos, listing metadata, or the sitter onboarding wizard, or how to improve i2i / u2i / u2u quality without blindly ingesting a new model.
marketplace-search-recsys-planning
Use this skill whenever planning, designing, reviewing, or improving search and recommendation systems for a two-sided trust marketplace built on OpenSearch — covers user-intent framing, product-surface architecture, index design, query understanding, retrieval strategy, ranking, search-plus-recs blending, measurement, and a dashboard-and-alerting layer for ongoing decision making. Triggers on tasks involving marketplace search, homefeeds, ranking, relevance tuning, OpenSearch query DSL, analyzers, synonyms, golden sets, NDCG, A/B testing, or diagnosing an existing retrieval system. Use this skill BEFORE marketplace-personalisation when planning new work; hand off when the diagnosed bottleneck is personalisation-specific.
review-change
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condition-based-waiting
This skill should be used when the user mentions "flaky tests", "race condition", "timing issues", "wait for", "test sometimes fails", or when tests have inconsistent pass/fail behavior. Replaces arbitrary timeouts with condition polling.
defense-in-depth
This skill should be used when the user asks for "defensive coding", "input validation", "prevent bugs", "multiple validation layers", or when fixing bugs caused by invalid data reaching deep execution. Validates at every layer.
finishing-a-development-branch
Guide completion of development work by presenting merge/PR options. Use when "I'm done", "merge this", "create PR", "finish up", or when implementation is complete and tests pass.
getting-started
This skill is loaded automatically at session start via SessionStart hook. Establishes protocols for finding and using skills, checking skills before tasks, brainstorming before coding, and creating tasks for checklists.
pragmatic-architecture
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receiving-code-review
This skill should be used when processing code review feedback, responding to reviewer comments, or when feedback seems unclear or technically questionable. Requires verification before implementing.
root-cause-tracing
This skill should be used when the user asks to "find the root cause", "trace the bug", "why is this happening", "where does this come from", or when errors occur deep in the call stack. Systematically traces backward to identify the source.
systematic-debugging
This skill should be used when the user reports a "bug", "not working", "fix this", "debug", "test failing", or when investigating unexpected behavior. Four-phase framework ensuring root cause understanding before attempting solutions.
test-driven-development
Use this skill when implementing any feature, bug fix, or plan task. Triggers on "write tests", "add a test", "do TDD", "test-driven", "implement with tests", "implement task", or when dispatched as a subagent for plan execution. Write test first, watch it fail, write minimal code to pass.
testing-anti-patterns
This skill should be used when reviewing test code, the user asks "is this test good", "test quality", "mock properly", or when tests behave unexpectedly. Identifies common testing mistakes.
verification-before-completion
This skill should be used when claiming a task is "done", "complete", "finished", "fixed", "passing", or before committing. Requires running verification commands before making success claims.
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