Menu
Extract non-obvious learnings from session to AGENTS.md files to build codebase understanding
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Design command-line interface parameters and UX: arguments, flags, subcommands, help text, output formats, error messages, exit codes, prompts, config/env precedence, and safe/dry-run behavior. Use when you're designing a CLI spec (before implementation) or refactoring an existing CLI's surface area for consistency, composability, and discoverability.
Update dependencies
Swift Concurrency review and remediation for Swift 6.2+. Use when asked to review Swift Concurrency usage, improve concurrency compliance, or fix Swift concurrency compiler errors in a feature or file.
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.
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.
Best practices and example-driven guidance for building SwiftUI views and components. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens, or needing component-specific patterns and examples.
Baseado na classificação ocupacional SOC
| name | learn |
| description | Extract non-obvious learnings from session to AGENTS.md files to build codebase understanding |
| metadata | {"author":"R44VC0RP"} |
Analyze this session and extract non-obvious learnings to add to AGENTS.md files.
AGENTS.md files can exist at any directory level, not just the project root. When an agent reads a file, any AGENTS.md in parent directories are automatically loaded into the context of the tool read. Place learnings as close to the relevant code as possible:
What counts as a learning (non-obvious discoveries only):
What NOT to include:
Process:
After updating, summarize which AGENTS.md files were created/updated and how many learnings per file.
$ARGUMENTS
