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Analyze relationships between people, objects, or papers as networks in Python. Use NetworkX to find shortest paths, identify important nodes and communities, visualize connections, exchange graph data, and generate sample networks for testing.
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Build interactive maps with AntV L7, a library for displaying geographic data. The skill guides data loading, points, routes, areas, heatmaps, map interactions, animations, and performance tuning for large datasets.
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Improve page titles, meta descriptions, and social sharing previews with multiple alternatives for A/B testing, which compares different versions. Check character counts and preview search results to assess how each option will appear.
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Helps select graph algorithms for shortest paths, minimum spanning trees, network flow, and coloring. Provides decision guides and example commands for symbolic calculations and checking mathematical properties.
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Guides authorized API security testing across authentication, access controls, unintended field updates, rate limits, and GraphQL. Helps agents define scope, review alternative testing directions, and organize request evidence for verified findings or reports of unsuccessful checks.
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Guide systematic security testing of Web applications and APIs across input handling, authentication, business rules, protocols, files, and deployment settings. Use topic-specific references and playbooks, or step-by-step testing guides, to choose checks suited to the target.
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Work with geographic points, lines, and areas in Python. Read spatial files, combine datasets by location, calculate areas and distances, transform coordinate systems, and export results as maps or converted files.
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Plan long-sequence training for MoE models, which divide work among expert networks, in Megatron Bridge. Use experiment-based guidance to balance parallelism, selective recalculation, and routing choices when investigating memory shortages or reduced training throughput.
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Configure Obsidian graph colors by tag, folder, category, or visibility by updating .obsidian/graph.json. Use for graph colorization; preserve other graph settings and back up before changes.
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Provides authoritative guidance on Amazon Neptune Database and Neptune Analytics for graph, knowledge-graph, and relationship-heavy workloads — fraud detection / fraud rings, agentic memory / chatbot context across sessions, recommendations, identity resolution, Gremlin / openCypher / SPARQL queries, supernode / slow traversal, Neo4j to Neptune migration / APOC compatibility, Neptune Database vs Analytics engine selection, PageRank / community detection, GraphRAG, and connectivity from Lambda / EC2 / applications. Creates and modifies Neptune Database clusters/instances and Neptune Analytics graphs on explicit user confirmation; blocks destructive operations (delete, reset-graph, failover, major upgrade) and redirects to change-control.
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Use whenever the agent needs to add, create, hand-author, patch, or place Motion Graphic JSX assets in a OpenChatCut project. This is the direct-authoring path: use create_motion_graphic_from_code / edit_asset / edit_item, not motion-graphic-gen or submit_motion_graphic. Covers project/timeline intake, project visual language, editable properties, asset binding, inline JSX authoring, existing asset updates, timeline placement, and verification.
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Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)
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Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).
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Use when the user types /agentlas-graph, /agentlas graph, or /hep-graph to create, list, inspect, or run Agentlas automation graphs.
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INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
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KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essenti
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Plan shoot-ready Amazon product photography, listing image sets, infographics, lifestyle scenes, and production briefs. Use when a seller asks for an Amazon photo shot list, creative direction, image-pack plan, photography budget, DIY-versus-done-for-you decision, or handoff to a photographer or image-generation workflow. Do not use for listing copy or image-only performance auditing.
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Membangun motion graphic sinematik di browser (promo video, opener, intro, bumper, kinetic typography, explainer/video penjelasan bergambar 16:9 atau 9:16) memakai HTML + CSS + GSAP (+ Three.js bila perlu), dengan hasil yang bergerak seperti video sungguhan — bukan slide presentasi. Gunakan skill ini setiap kali user meminta "video promo", "opener", "intro animasi", "motion graphic", "bumper", "kinetic typography", "animasi teks sinematik", "explainer", "video penjelasan" (jurnalisme visual, kartun edukasi, kolase), atau menunjukkan referensi video promosi/explainer dan ingin dibuatkan versi web-nya — bahkan bila mereka tidak menyebut kata "motion graphic" secara eksplisit. Juga gunakan bila user mengeluh hasil animasi web "seperti PPT/presentasi" dan ingin lebih sinematik, atau ingin merender animasi web menjadi file video MP4, atau ingin explainer kartun/animasi dibangun LANGSUNG di After Effects lewat bridge/MCP Higgsfield.
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Use `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships. USE FOR: graphify commands; graph JSON, HTML, SVG, Cypher, Markdown, and Obsidian exports; repository map and architecture snapshot generation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Create distinctive Photo Relic editorial artworks from user-provided photographs: preserve the real photo and pair it with a recognizable, artful abstract relic shaped like memory, modern printmaking, quiet Eastern restraint, and source-derived light. Use when the user asks to turn a photo into minimal art, photographic relic posters, abstract editorial photography, gallery-like photo posters, Douyin-ready art series covers, graphic photo abstraction, afterimage compositions, or similar visual treatments while keeping the original photograph truthful.
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Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from a code knowledge graph. Applies when a `.codegraph` index exists in the workspace, or when the user wants to create one.
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GraphQL API specialist for schema design, resolvers, federation, and performance optimizationUse when "graphql, schema design, resolvers, federation, apollo, relay, dataloader, n+1 problem, graphql security, graphql, api, schema, resolvers, federation, subscriptions, apollo, relay, dataloader" mentioned.
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Route HugeGraph MCP operational checks to status, schema, MCP read-only state, AI availability, and read-only verification tools. Use when the user asks to check the current graph, schema, MCP connection, readonly state, HugeGraph-AI state, counts, indexes, or readiness.
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Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.
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