285건 · 관련도순
Design and build visual stories where scrolling changes charts, maps, or video. Plan meaningful scene transitions, choose suitable implementation tools, and provide mobile layouts and static alternatives for readers who prefer reduced motion.
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Query images with a local Ollama vision model without loading the image into the main agent context. Use when you need to describe a screenshot, check whether rendered content is present, detect overlapping elements, or ask any visual question about a PNG/JPEG/WebP file. Requires Ollama running locally with the Gemma 4 multimodal model (`gemma4` on Ollama). Script: .agents/skills/vision/scripts/ask.py. Trigger phrases: "describe image", "what does this screenshot show", "does the canvas contain content", "check screenshot visually", "look at this image", "any overlapping elements", "vision query".
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React 18 patterns for LlamaFarm Designer. Covers components, hooks, TanStack Query, and testing.
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Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.
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RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.
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CLI best practices for LlamaFarm. Covers Cobra, Bubbletea, Lipgloss patterns for Go CLI development.
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Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
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Shared Go best practices for LlamaFarm CLI. Covers idiomatic patterns, error handling, and testing.
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Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.
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Manage LlamaFarm worktrees for isolated parallel development. Create, start, stop, and clean up worktrees.
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Electron patterns for LlamaFarm Desktop. Covers main/renderer processes, IPC, security, and packaging.
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Designer subsystem patterns for LlamaFarm. Covers React 18, TanStack Query, TailwindCSS, and Radix UI.
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Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework. Activate when the calling agent must build, debug, harden, or evaluate a Retrieval-Augmented Generation pipeline over unstructured/private data, decide between RAG primitives (Index types, retrievers, query engines, routers, agents), or pick LlamaIndex vs LangChain / Haystack / raw vector store for a coding task. Encodes the 5-layer mental model (Documents → Nodes → Indices → Retrievers → Query Engines / Response Synthesizers), the canonical RAG bootstrap SOP from baseline `VectorStoreIndex` through hybrid + reranker + eval-loop hardening, the official 13-failure-mode checklist, and 5 dilemma cases distilled from docs, GitHub issues, and 2025 production post-mortems.
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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
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Select appropriate Ollama models for processing sensitive but legal content. Use when: (1) llama3.2 or deepseek-r1 refuses to process content with "I cannot assist" responses, (2) Local LLM returns generic safety disclaimers instead of following instructions, (3) Need to process adult content, sex work data, or other legal-but-sensitive material through a local LLM. Also covers using /api/chat vs /api/generate for system prompt support, and structuring prompts for consistent format compliance.
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Use when building RAG or LLM applications with LlamaIndex - data loaders, node parsing, vector stores, retrievers and rerankers, query engines, agents and workflows, streaming, or evaluation
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Use when integrating an app with local AI models through Ollama — connection checks, model listing/selection, local-only mode, cloud-fallback consent, visible run states, and recovering from Ollama errors.
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Operational guide for the NV oOS WordPress Playground demo blueprints — the Content Graph "Project Asteria" demo, the Complete bundle × local Ollama demo, and the Docs Hub wp.org Live Preview demo. Covers blueprint authoring patterns (embedded runPHP seed snippets, generator scripts, preview-safe vs standalone split), CORS hosting gotchas, the CI Plugin Check gate (built-ZIP scan, rsync/distignore sync, ABSPATH guards), Playground worker crash modes (PHP-side localhost fetches, inline-script UTF-8, SPA SSE-hold mount bursts, crash-truncation SyntaxErrors), local Ollama integration (OLLAMA_ORIGINS, browser policy matrix, plugin settings + assistant meta keys), and the CLI validation harness (probe builder, mount quirks, server-mode 502 boot). Use when extending or debugging the demo blueprints, adding a new Playground demo, or triaging a crashing Playground instance.
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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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기존 웹 앱에 자연어로 화면을 조작하는 AI 도우미를 추가하도록 돕습니다. 설치와 조작 패널 표시부터 LLM 연결, 동작 확인, 정식 배포 시 설정까지 안내합니다.