swiftui-expert-skill
Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns. Also triggers whenever an Xcode Instruments `.trace` file is referenced (to analyse it) or the user asks to **record** a new trace — attach to a running app, launch one fresh, or capture a manually-stopped session with the bundled `record_trace.py`. A target SwiftUI source file is optional; if provided it grounds recommendations in specific lines, but a trace alone is enough to diagnose hangs, hitches, CPU hotspots, and high-severity SwiftUI updates.
95
92%
Does it follow best practices?
Impact
100%
1.16xAverage score across 3 eval scenarios
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that clearly defines a specific niche (SwiftUI development + Xcode Instruments performance analysis), lists concrete actions, and provides explicit trigger conditions. It covers both the code quality/writing aspect and the performance diagnostics aspect with natural keywords users would employ. The description is detailed without being padded, and uses appropriate third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: write/review/improve SwiftUI code, analyze .trace files, record new traces, attach to running apps, launch fresh, capture manually-stopped sessions, diagnose hangs/hitches/CPU hotspots/high-severity SwiftUI updates. Very detailed and actionable. | 3 / 3 |
Completeness | Clearly answers both 'what' (write/review/improve SwiftUI code, analyze trace files, record traces, diagnose performance issues) and 'when' ('Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns. Also triggers whenever an Xcode Instruments .trace file is referenced...'). Explicit trigger guidance is provided. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms: 'SwiftUI', 'Xcode Instruments', '.trace file', 'macOS', 'iOS 26+', 'Liquid Glass', 'state management', 'view composition', 'refactoring', 'hangs', 'hitches', 'CPU hotspots', 'record_trace.py'. These are terms users would naturally use when requesting help in this domain. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche combining SwiftUI development with Xcode Instruments trace analysis. The specific mention of iOS 26+ Liquid Glass, macOS-specific APIs, record_trace.py, and .trace files makes this very unlikely to conflict with generic coding or other platform-specific skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, comprehensive SwiftUI skill that excels at progressive disclosure and workflow clarity. The Topic Router pattern is an effective navigation mechanism, and the trace recording/analysis workflows are particularly strong with concrete CLI commands and decision logic. The main weakness is moderate redundancy between the Topic Router table and the References section, plus some explanatory prose in the trace workflows that could be trimmed given the linked reference files.
Suggestions
Remove or consolidate the References section at the bottom since it largely duplicates the Topic Router table — or differentiate them clearly (e.g., make References a quick-lookup list without descriptions, and keep the Topic Router as the authoritative routing table).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly efficient for its breadth, but there's notable redundancy: the References section at the bottom duplicates the Topic Router table almost verbatim, and some workflow descriptions (e.g., trace recording) include explanatory prose that could be trimmed since the detailed reference files are already linked. The Correctness Checklist is lean and valuable. | 2 / 3 |
Actionability | The skill provides concrete, executable bash commands for trace recording and analysis, specific code patterns in the correctness checklist, and clear decision logic (e.g., simulator vs real device template selection). The Topic Router gives precise file paths. Workflows are copy-paste ready with actual CLI invocations and flags. | 3 / 3 |
Workflow Clarity | Multi-step workflows are clearly numbered with explicit validation checkpoints. The trace recording workflow has a clear sequence (confirm target → pick template → start → signal stop → analyse). The trace analysis workflow includes scoping decisions, window resolution, interpretation steps with specific thresholds (e.g., <25% = blocked), and a feedback loop for grounding in source. The review/improve workflows also have clear sequencing. | 3 / 3 |
Progressive Disclosure | The skill is an excellent overview document that delegates detailed content to 20+ well-organized reference files via a clear Topic Router table. References are one level deep, clearly signaled with consistent paths, and the skill body contains just enough context to route correctly without inlining the reference content. Navigation is easy via the table format. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- avdlee/swiftui-agent-skill
- Commit
0066966
- Reviewed
Table of Contents
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