Implement server APIs, authentication, and application data access. Schema modeling and query tuning use oma-db.
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1.1천건 · 관련도순
Implement server APIs, authentication, and application data access. Schema modeling and query tuning use oma-db.
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Hermes Agent (Nous Research の AI CLI エージェント)。インストール、 CLI コマンド (chat, model, gateway, config, cron, webhook, mcp, skills, profile, hermes pm)、 Configuration (Terminal Backends, Memory, TTS / STT, Auxiliary Models, Compression, Display, Local Models llama.cpp, Egress / Secrets)、 Features (Tools, Skills, Hooks, Delegation, Kanban, Cron, Voice Mode, Personality, Context Files)、 Messaging Gateway (Platform Support, Bot Mode, Connectors)、Security、Architecture、 Hermes Desktop、Plugin Catalog、Profiles、Developer Guide、Nous Portal (Tool Gateway)。
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Rust 製 AI/ML ライブラリ fandhe-ai のリファレンス。Burn / candle / tch 非依存の from-scratch 実装。 tape(), tape_for, Tape, Gradients, Tensor, Var, LinearVars, autodiff, kernel fusion, FusionPlan, BackendOps, Device (Cpu / Cuda / Metal), DeviceParamStore, compat::array, compat::Sequential, nn::Module, optim (AdamW / GradScaler), data::DataLoader, ONNX import / export, safetensors, inference::generate / KvCache, guardrail / self-repair CLI。
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Harden iOS/Android apps you ship: storage, TLS pinning policy, IPC, and backend trust. You still enforce authz on the server.
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Provides expert knowledge of Spring Boot conventions, Kotlin idioms, and MVC patterns for backend API development.
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Design, implement, and review web interface layout, component states, feedback, and motion within the current CodeConductor workflow. Use for concrete web UI work or requested UI audits, not backend-only tasks or native mobile apps.
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Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
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Kotlin/Spring Boot 3.x patterns - use for backend services, REST APIs, dependency injection, controllers, and service layers
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Provides and generates complete CRUD workflows for Spring Boot 3 services. Creates feature-focused architecture with Spring Data JPA aggregates, repositories, DTOs, controllers, and REST APIs. Validates domain invariants and transaction boundaries. Use when modeling Java backend services, REST API endpoints, database operations, web service patterns, or JPA entities for Spring Boot applications.
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Builds reusable Convex components with isolated tables and app-facing APIs. Use for new components, reusable backend modules, integrations, or component boundary work.
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Deploy containerized frontend + backend applications to Azure Container Apps with remote builds, managed identity, and idempotent infrastructure.
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Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.
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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
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Goal-integrity skill. Use for backend/API/persistence, preserve/do-not-change, tests/validation, mocks, rework, multi-part requests. Emits Goal Contracts, Deviation Notices, Phase Checks, Final Audits. Skip for Q&A or trivial edits.
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Base skill for Refly ecosystem: creates, discovers, and runs domain-specific skills bound to workflows. Routes user intent to matching domain skills via symlinks, delegates execution to Refly backend. Use when user asks to: create skills, run workflows, automate multi-step tasks, or manage pipelines. Triggers: refly, skill, workflow, run skill, create skill, automation, pipeline. Requires: @refly/cli installed and authenticated.
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Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
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Use when the user wants a UI-only action plan — components, pages, composables/hooks, state, forms and their E2E coverage — 'plano de frontend para a tela X', 'plan the settings page'. Writes .planning/feat/features/{slug}/plan.md with E2E scenarios and playwright-cli checks. Do NOT use for API/database work (feat-backend), full features (feat-feature), writing code (feat-exec) or UI review (feat-review).
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Use when the user wants a small, well-bounded change done now without a plan file — a bugfix, config change, rename, doc update or simple refactor touching 1–5 files — 'corrigir rapidinho', 'quick fix no X', 'renomear Y'. Presents a mini-plan, implements after approval, verifies and commits. Do NOT use for more than 5 files, architectural decisions, migrations or new UI flows (use feat-feature / feat-backend / feat-frontend).
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Use when the user wants to execute an existing pwdev-feat action plan — 'executar o plano user-crud', 'exec latest', 'rodar o plano', 'retomar a execução'. Dispatches the executor (subagent when the runtime has one, inline otherwise) in IMPLEMENT or REPORT mode, handles NEEDS_ADVICE with the advisor, and supports --resume. Do NOT use to create plans (feat-feature, feat-backend, feat-frontend, feat-test, feat-review) or for tasks without a plan (feat-quick).
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Derive and implement first-principles audio-coupled haptic and kinetic UI feedback. Use when designing, reviewing, or coding haptics/audio for mobile apps, native iOS/Android, React Native/Expo, SwiftUI, games, detent pickers, toggles, sliders, page curls, scroll gestures, wallet/signature flows, Solana transactions, backend/realtime state changes, confirmations, settlements, and semantic UI events where feedback should follow signal math instead of ad hoc vibration calls.
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Bun runtime and modern JavaScript backend practices, including Bun-native tooling (bun run/test/build) and PostgreSQL usage guidance. Use when building or reviewing Bun-based services, APIs, scripts, or when Bun-specific workflow questions arise.
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Local ComfyUI / Stable Diffusion SDXL partial-asset generation workflow. Use for ComfyUI, stable diffusion, SDXL, LoRA, badge, cap, plaque, panel fragment, UCUF partial asset exploration, and saving generated PNGs from the local backend.
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Measure, profile, and fix performance bottlenecks — Core Web Vitals, backend latency, bundle size, and database queries. Load when performance requirements exist, users report slowness, profiling reveals bottlenecks, or the user asks to optimize load time, LCP, INP, CLS, or response time. Not for premature optimization without evidence. Pairs with browser-testing-with-devtools and ci-cd-and-automation for regression guards.
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