4.1천건 · 관련도순
Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing A...
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Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning Use when: adding search to, algolia, instantsearch, search api, search functionality.
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AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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Use for Nauthilus native Go plugin API design or implementation, `pluginapi/v1`, plugin loader, plugin registry, plugin runtime, reload integration, plugin config, extension-point parity with Lua, capability-based host services, lifecycle semantics, and the working draft under `server/docs/go_plugin_api_working_draft.md`.
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Plan or review FriendlyBet architecture, implementation, schema, data flows, scoring, provider integrations, static/PWA behavior, Supabase/RLS impact, migrations, automation, and technical sequencing. Use when a task asks how to build, refactor, generalize, integrate, test, or safely ship FriendlyBet code.
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Systematic ambiguity resolution through tiered information gathering. Use when facing unclear requirements, unknown context, uncertain implementation choices, or any situation where guessing would be risky.
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Orchestrate operational workspace setup before implementation slices across scaffold, CI/CD, hosting, and data provisioning shards
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Cross-session progress tracking, pattern extraction, and session resumption. Gives agents memory across sessions using markdown files in `.memory/pipeline/progress/`. Subsumes self-improving-agent — handles both implementation tracking AND experiential learning in one skill. Workflows invoke specific protocols by name.
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Orchestrate single-slice implementation via setup and strict TDD passes with mandatory progress tracking updates
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Structured methodology for adversarial thinking — generating attack scenarios, abuse cases, race conditions, and security edge cases against specs and implementations. Produces spec-level gap items, not code-level fixes.
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Use before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
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Validate implementation prerequisites, load slice/spec context, detect execution mode, and write contract schemas before TDD execution
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Optimize a single Jetpack Compose @Composable function. Use when the user wants to improve, polish, animate, or refactor ONE Composable — keywords like "optimize this composable", "make this smoother", "add animation to this", "split this composable", "fix recomposition", "this composable is laggy", "polish this UI", or when user pastes/points to a single @Composable function. Analyzes the target for recomposition issues, missing animations, size/concern splits, and stability problems, then iterates with the user via AskUserQuestion to pick which optimizations to apply, then delegates implementation to the kta-compose-developer agent and summarizes changes. Input MUST be exactly one Composable (file path + function name, or function name alone).
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Use this skill for all verification: unit, component, E2E, native, and release checks. Required alongside mobile-core for every implementation.
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Use this skill for any Ionic Vue + Capacitor mobile work: Vue architecture, Composition API, TypeScript, state, env config, shared conventions. Required for every implementation task alongside mobile-testing.
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Engineering operating model for teams where AI agents generate a large share of implementation output.
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Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.
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Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context
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Receive and act on code review feedback with technical rigor, not performative agreement or blind implementation
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Execute implementation plan by dispatching fresh subagent for each task, with code review between tasks
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Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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Dispatch code-reviewer subagent to review implementation against plan or requirements before proceeding
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Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
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Translate Figma designs into production-ready application code with 1:1 visual fidelity. Use for Figma URLs, node IDs, implementation requests, or components that must match Figma specs; use the local `figma` skill for general Figma MCP context and setup.
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