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Found 3,051 Skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Generate CLAUDE.md and AGENTS.md by exploring the codebase
Summarize the objectives, structure, constraints, naming and collaboration rules of the entire project to form reusable project-level specification documents
API reference: SwiftUI. Query for views, layouts, navigation, @State/@Binding/@Observable, view modifiers, NavigationStack, iOS 26+ features.
API reference: UIKit. Query for UIView, UIViewController, controls, table and collection views, navigation controllers, scenes, Auto Layout, images, colors, gestures, presentation, and SwiftUI hosting.
Scan code and specs for drift, directly synchronize spec files, and report the gaps in chat.
Analyze codebase with parallel mapper agents to produce .planning codebase documents
Create well-structured RFCs and technical proposals for software projects. Use this skill whenever the user wants to write an RFC, technical proposal, design doc, architecture doc, or system design overview. Also trigger when the user says things like "write an RFC", "I need to propose a new system", "create a technical proposal", "document the architecture", "write up the design", "I need a design doc", or "explain the system architecture in a doc". Even if they just say "RFC", "design doc", or "arch doc", use this skill. Covers both RFCs (proposing what to build) and architecture docs (documenting an existing codebase).
Generate interface documents for Triton operators of Ascend NPU. Used when users need to create or update interface documents for Triton operators of Ascend NPU. Core capabilities: (1) Generate standardized documents based on templates (2) Support the list of Ascend NPU product models (3) Provide specifications for operator parameter descriptions (4) Generate call example frameworks.
Maps the full customer journey from first touch to advocacy. Generates a comprehensive customer-journey.md with all stages, touchpoints, emotions, pain points, opportunities, Mermaid diagrams, and metrics. Use when mapping customer experience, designing onboarding flows, identifying churn risks, or optimizing conversion funnels.
Document finalized technology selections, architecture decisions, long-term constraints, and coding conventions in the project into searchable permanent documents. No one will remember why X was chosen six months later, but with decision documents, at least the background can be understood before making changes next time. Four types: tech-stack (which tools/libraries/frameworks to use), architecture (how the system is organized), constraint (what is not allowed), convention (what is uniformly done). Trigger scenarios: Proactively push when important choices are made after feature-design or issue-analyze, or when the user says "record decision", "archive technology selection", "ADR", "record this constraint", "write down the convention". Only archive finalized decisions; do not archive under-discussion solutions.
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, so that both AI and humans can look them up when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — bugs, configuration traps, environment issues, integration failures; The knowledge track records findings that "should be the default approach going forward" — best practices, workflow improvements, reusable patterns. Trigger scenarios: Proactively prompt for input when wrapping up feature-acceptance or issue-fix, or when the user says phrases like "document knowledge", "learning", "document learnings", "record this experience". Spec documents record what was done and how it was done, while learning documents record what pitfalls were encountered / what was learned — the two complement each other and are not interchangeable.