'muse' 검색 결과

Application performance monitoring — transactions, profiling, and finding slow code — works with any APM platform.

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Build with BAAI's Aquila models — open bilingual models from Beijing's academy with research transparency.

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Idiomatic Astro: islands architecture, content collections, SSR/SSG choices, and performance-first builds. Use when writing, reviewing, or structuring Astro sites.

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Design tools for AI agents — clean function interfaces, typed schemas, informative errors, idempotency, and tool documentation. Use when giving an agent new capabilities or fixing flaky tool use.

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Build reusable agent workflow patterns — subagents with scoped briefs, event hooks, slash commands, and session management. Use when turning one-off agent tasks into repeatable, composable workflows.

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Run goal-driven autonomous agent loops — decomposing objectives, executing tool chains, self-critiquing, and iterating until done. Use when exploring what fully autonomous task execution looks like and its limits.

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Coordinate teams of role-based agents — role definitions, task delegation, sequential and hierarchical workflows, and shared memory. Use when a job naturally splits into specialist roles collaborating.

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Build LLM applications with chain-style orchestration frameworks — prompts, chains, tool-calling agents, memory, and retrieval pipelines. Use when structuring multi-step LLM programs, adding tools to a model, or composing RAG systems in code.

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Build data-centric LLM applications with indexing and retrieval frameworks — document ingestion, indices, query engines, and RAG pipelines. Use when the core problem is getting the right data in front of the model.

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AI agent guidance — agent architecture, tool design, planning loops, guardrails, evaluation, and production agents.

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Architect autonomous agent systems — perception/action loops, tool design, planning strategies, memory, and multi-agent orchestration patterns. Use when designing an agent from scratch or scaling a prototype to production.

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Design and build LLM agents: ReAct loops, tool schemas, planning, memory, guardrails, evals, and human-in-the-loop. Use when building autonomous multi-step AI systems.

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Argo CD guidance — GitOps workflows, Application manifests, sync strategies, AppProjects, and multi-cluster ops.

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Build AI chatbots end to end — conversation design, persona, retrieval grounding, escalation, and deployment. Use when creating a chatbot for support, sales, or internal assistance.

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Ship AI features to production — model selection, evals, latency/cost optimization, guardrails, monitoring, and iteration loops. Use when turning an LLM prototype into a reliable product feature.

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Craft effective AI image prompts with structured syntax, style control, and iterative refinement techniques.

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Practice AI safety across the lifecycle — risk assessment, alignment concepts, evaluation, deployment safeguards, and governance. Use when building or deploying AI systems responsibly.

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Build streaming AI user interfaces with AI SDK patterns — message rendering, tool-call displays, loading states, and optimistic updates. Use when creating chat UIs that stream model output and show agent activity.

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Use when a task needs the judgment of a museum or gallery curator — evaluating whether to accept a donated collection or object, writing an acquisition or deaccession recommendation, resolving a provenance or repatriation question, deciding a loan request, or drafting exhibition label copy.

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Create museum-quality visual art through design philosophy. Generate original visual designs, posters, and artwork as PDFs or PNGs using sophisticated aesthetic movements and expert-level craftsmanship.

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Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40+ derived EXG scores) into responses. Requires a BCI wearable (Muse 2/S or OpenBCI) and the NeuroSkill desktop app running locally.

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Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40+ derived EXG scores) into responses. Requires a BCI wearable (Muse 2/S or OpenBCI) and the NeuroSkill desktop app running locally.

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Generate a single-file industrial-archive product landing page (Nordic museum aesthetic, hash-routed detail pages). Takes a natural-language description of one or more "exhibit-style" products (objects, tools, hardware, watches, kitchenware, lighting, audio, instruments, anything with a designed/forged/restrained quality); outputs ONE working .html file. Visitors see a black-framed cover that flips between exhibits, sidebar index, side meta column (material/origin/year/dimension), and click any exhibit → full detail page (giant italic title, spec table, hero image, lead + 3 prose paragraphs, gallery, prev/next). Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger: "做个工业风产品落地页", "做克制之物风格的展品页", "industrial-archive-gen ...", or when user drags this skill folder into chat asking for a product page in the Nordic-industrial archive style.

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