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Found 6,915 Skills
Front door of the SDD flow. When the user asks for a feature or bug fix ("implementa…", "agrega…", "arregla…", "add…", "build…", "fix…"), FIRST scan the request + codebase context for load-bearing ambiguity and ask a few targeted clarifying questions (selectable options, recommended first) BEFORE writing any spec or code — then hand a well-formed goal to /opsx:propose (small) or the sdd-feature-flow workflow (large). Skip the questions when the request is already unambiguous. Modeled on GitHub Spec-Kit's /clarify.
Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
Design and build game UI/UX — HUDs, menus, and overlays — that survive every screen: anchor- based responsive layout, resolution/aspect scaling and safe areas, keyboard/gamepad focus navigation, a screen/menu state stack, and event-driven (not polled) HUD updates. Engine- neutral patterns that pair with the detected engine's UI skill. Use when the user mentions HUD, health bar, main menu, pause menu, settings screen, UI layout, anchors, UI scaling, aspect ratio, safe area, controller/keyboard menu navigation, or wiring UI to game state.
Builds a content-addressed semantic-unit index from source code for structural context. Use when a pinned or live codebase is available and structural cross-reference data would improve research quality. Don't use for findings analysis, patching, or reporting.
Drives a disciplined explore → plan → implement → verify loop for changing an AI agent's behavior with confidence — whether fixing a reported failure or introducing a new requirement, business rule, or policy. Grounds the diagnosis in MLflow traces, codifies the desired behavior as a regression test suite (`mlflow.genai.evaluate` assertions in `@mlflow.test` pytest tests), and iterates the agent — not the test — until green, resisting quick system-prompt patches when the real fix is upstream (missing tool, retrieval source, or capability). Use whenever the user wants to fix or change how an agent behaves — e.g. "fix this issue in my agent", "this answer is wrong", "the agent is hallucinating", "improve my agent based on this trace", "make the agent do X instead of Y", "I want the agent to lead with/prioritize/recommend X", "new business rule: the agent should X", "always/never do X", "change the agent's default behavior" — or shares a trace they want addressed.
Provides instructions and architectural patterns for migrating Android TV applications from legacy Leanback UI Toolkit, Android Views, or Support Fragments to Jetpack Compose for TV (androidx.tv). Use this skill for Leanback to Compose migrations, including browse screen, settings screen, authentication screen, login screen, or video playback screen migrations, or when replacing BrowseSupportFragment, LeanbackSettingsFragment, PreferenceFragment, BaseLeanbackPreferenceFragmentCompat, VideoSupportFragment, GuidedStepSupportFragment, SearchSupportFragment, VerticalGridSupportFragment, Presenter, ArrayObjectAdapter, or CursorMapper with modern Compose equivalents, implementing immersive carousels with focus memory, Media3 video playback with PlayerSurface, or custom 10-foot hero layouts.
Suggest and validate semantic dictionary (SD) mappings for audit log integrations using raw vendor log payloads or live ingested events. Use when: mapping a vendor audit log feed, authentication logs, user activity logs to the Dynatrace SD; checking required semantic fields; proposing OpenPipeline processor extraction rules based on DQL; running runtime validation (fetches live logs by log.source, then applies static validation).
This skill should be used when the user asks about libraries, frameworks, API references, or needs code examples. Activates for setup questions, code generation involving libraries, or mentions of specific frameworks like React, Vue, Next.js, Prisma, Supabase, etc.
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
Implement authentication and authorization with Better Auth - a framework-agnostic TypeScript authentication framework. Features include email/password authentication with verification, OAuth providers (Google, GitHub, Discord, etc.), two-factor authentication (TOTP, SMS), passkeys/WebAuthn support, session management, role-based access control (RBAC), rate limiting, and database adapters. Use when adding authentication to applications, implementing OAuth flows, setting up 2FA/MFA, managing user sessions, configuring authorization rules, or building secure authentication systems for web applications.
Example scaffolding and checklists for developing Home Assistant custom integrations. Use when building or reviewing a custom integration based on the included example templates.
Comprehensive Vue.js development skill covering Composition API, reactivity system, components, directives, and modern Vue 3 patterns based on official Vue.js documentation