Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Audits SwiftUI performance: rendering, scrolling, CPU and memory, unnecessary view updates, body re-evaluations, and layout thrashing, with Instruments guidance when code review is inconclusive. Use when a SwiftUI screen stutters, scrolls poorly, or uses too much CPU.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Attribution: Sourced from steipete/agent-scripts by Peter Steinberger. Originally created by @Dimillian from Dimillian/Skills (2025-12-31).
Audit SwiftUI view performance end-to-end, from instrumentation and baselining to root-cause analysis and concrete remediation steps.
Collect:
Focus on:
id churn, UUID() per render).body (formatting, sorting, image decoding).GeometryReader, preference chains).Explain how to collect data with Instruments:
Prioritize likely SwiftUI culprits:
id churn, UUID() per render).body (formatting, sorting, image decoding).GeometryReader, preference chains).Apply targeted fixes:
@State/@Observable closer to leaf views).ForEach and lists.body (precompute, cache, @State).equatable() or value wrappers for expensive subtrees.body// ❌ Slow allocation on every render
var body: some View {
let number = NumberFormatter()
Text(number.string(from: 42)!)
}
// ✅ Cached formatter
final class Formatters {
static let number = NumberFormatter()
}
// ❌ UUID() per render — destroys identity
ForEach(items, id: \.self) { item in Row(item) }
// ✅ Stable Identifiable ID
ForEach(items) { item in Row(item) }
// ❌ Runs on every body eval
List {
ForEach(items.sorted(by: sortRule)) { item in Row(item) }
}
// ✅ Sort once before view updates
let sortedItems = items.sorted(by: sortRule)
// ❌ Whole view tree re-renders on any items change
@Observable class Model { var items: [Item] = [] }
var body: some View { Row(isFavorite: model.items.contains(item)) }
// ✅ Granular view models or per-item state
Ask the user to re-run the same capture and compare with baseline metrics. Summarize the delta (CPU, frame drops, memory peak) if provided.
Provide:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
日本語の概要は準備中です。原文の説明を表示しています。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
日本語の概要は準備中です。原文の説明を表示しています。
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
日本語の概要は準備中です。原文の説明を表示しています。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
日本語の概要は準備中です。原文の説明を表示しています。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
日本語の概要は準備中です。原文の説明を表示しています。