4.2천건 · 관련도순
Guide authorized API security assessments from endpoint discovery to documented findings. Use a staged workflow to examine authentication, access permissions, input handling, data exposure, and request limits across REST, GraphQL, WebSocket, and SOAP APIs.
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Guide authorized security assessments of REST, SOAP, and GraphQL APIs. Organize endpoint discovery, authentication checks, access control tests, and input testing, then document discovered weaknesses and evidence of unauthorized data access.
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Compare GraphQL and RPC contracts, which describe expected API behavior, with generated clients and live handlers in a CTF sandbox. Identify hidden or outdated operations and preserve minimal request pairs that demonstrate the mismatch.
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Choose how an API, the interface software uses to exchange data, should work. Covers REST, GraphQL, and tRPC selection, consistent responses, pagination, versioning, authentication, request limits, documentation, and security review considerations.
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Design GraphQL APIs with clear data types, data-fetching functions called resolvers, and real-time updates. Address repeated database calls, pagination, structured errors, and expensive queries while planning schema changes that preserve compatibility.
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Test and debug REST and GraphQL APIs using curl, httpie, Postman collections, or scripted tests. Check authentication, invalid inputs, pagination, and response details to identify failures that a successful status code alone may miss.
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Work through unresolved review comments across dependent PRs managed with Graphite. Review branches from the base upward, propose fixes or replies for approval, test changes, and commit each branch locally while preserving stack dependencies.
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Connect static analysis results and human audit notes to a Trailmark code graph. Group findings by severity and compare them with input flow, impact, and privilege boundaries to prioritize investigation and understand findings in their code context.
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Turn text or structured data into infographics with selected layouts and visual styles. The skill can refine image prompts and, across multiple generation rounds, review the images and rank the results for selection.
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Check citations in LaTeX and Quarto manuscripts against a bibliography file. Find missing references, unused entries, and likely citation key typos, then flag incomplete fields, author formatting problems, and character encoding issues.
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Codebase'i knowledge graph olarak analiz et. Dependency, call graph, hotspot analizi.
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PyTorch Geometric (PyG) for graph neural networks: node/graph classification, link prediction with GCN, GAT, GraphSAGE, GIN. Message passing, mini-batches, heterogeneous graphs, neighbor sampling, explainability. Supports molecules (QM9, MoleculeNet), social/knowledge graphs, 3D point clouds. For non-graph DL use PyTorch; for classical graph algorithms use NetworkX.
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Use DIG (Dive into Graphs) to load graph-learning datasets, run graph generation, self-supervised learning, GNN explainability, 3D graph learning, GOOD OOD datasets, graph augmentation, fair graph learning, and large-scale graph workflows.
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Render Obsidian-style weighted graph views from book JSON, keyword indexes, TOCs, card data, or node-link data. Use when the user asks for Obsidian graph view, graph view png, weighted graph, keyword graph, directory-keyword graph, spherical graph visualization, or high-weight nodes centered with clear Chinese labels.
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World-class motion graphics expertise combining the animation principles of Disney, the kinetic typography of MK12, and the visual storytelling of studios like Buck and Ordinary Folk. Motion graphics transforms static ideas into dynamic visual experiences. Great motion graphics doesn't just move—it communicates. Every animation should have purpose: to guide attention, reinforce message, create emotion, or clarify concept. The best motion designers understand that restraint is power, that timing is everything, and that the animation should be invisible—viewers should feel the story, not notice the effects. Use when "motion graphics, animation, animate, motion design, kinetic, logo animation, title sequence, lower thirds, animated, after effects, lottie, transitions, motion, motion, graphics, animation, after-effects, lottie, kinetic, typography, design" mentioned.
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Knowledge graph specialist for entity and causal relationship modelingUse when "knowledge graph, graph database, falkordb, neo4j, cypher query, entity resolution, causal relationships, graph traversal, graph-database, knowledge-graph, falkordb, neo4j, cypher, entity-resolution, causal-graph, ml-memory" mentioned.
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Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.
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Use this skill when the user wants to turn code graph analysis into tracked GitHub issues — "audit the architecture", "find god nodes", "triage architectural debt", "run graphify and log issues", "what's over-coupled in this codebase", "create issues from graphify findings", "check for structural problems", "scan for architectural smells", or any request that combines codebase topology analysis with issue tracking. This skill runs graphify to build a dependency graph, parses GRAPH_REPORT.md for god nodes and structural patterns, converts findings into GitHub issue payloads, and optionally pushes them to the repo. It bridges static analysis and project management in a single automated pass. Requires graphify and gh CLI.
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Extract business areas, workflows, and process steps from a codebase and display them as an interactive horizontal flow graph. Use an existing knowledge graph, a map of project components, or run a lightweight scan of project files.
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Audit the titles, descriptions, images, and URLs shown when web pages are shared on social networks or messaging apps. Check Open Graph metadata, the tags that define link previews, for missing values and incorrect settings.
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Build, analyze, and visualize relationship data in Python with NetworkX. Find shortest routes, identify important nodes and groups, generate networks for simulations, and exchange graph data through tables and common file formats.
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Turn notes, prose, code, schemas, or tables into editable diagrams, including flowcharts, architecture diagrams, and schedules. Choose Mermaid, Graphviz DOT, PlantUML, or SVG to suit the content, with image or PDF rendering when needed.
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Integrate Microsoft Graph SDK into .NET, TypeScript/JavaScript, or Python applications to access Microsoft 365 data. Covers authentication, permissions, paginated results, incremental synchronization, change notifications, and retries when requests hit service limits.
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Extract references between imported documents and classify how they relate, such as relying on, extending, or refuting another work. Store these relationships as typed links so explicit graph queries can trace connections through the collection.
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