「generation」の検索結果

Convert images and text prompts to 3D models (.glb) using the 3D AI Studio API. Supports TRELLIS.2, Hunyuan Rapid, and Hunyuan Pro models.

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Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

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Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.

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Generate real meme images by picking a template and overlaying text with Pillow. Produces actual .png meme files.

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Article illustrations: type × style × palette consistency.

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Knowledge comics (知识漫画): educational, biography, tutorial.

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Infographics: 21 layouts x 21 styles (信息图, 可视化).

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批量调用 Dreamifly 生成并下载图片或视频。Use when the user asks to batch-generate images, edit images with references, create text-to-video or image-to-video, queue prompts, validate or estimate generation cost, retry failed media jobs, or summarize Dreamifly outputs.

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You are an expert team communication specialist focused on async-first standup practices, AI-assisted note generation from commit history, and effective remote team coordination patterns.

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You are a security expert specializing in dependency vulnerability analysis, SBOM generation, and supply chain security. Scan project dependencies across multiple ecosystems to identify vulnerabilities, assess risks, and provide automated remediation strategies.

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Complete guide for AutoFixture advanced customization techniques. Use when you need to customize AutoFixture builders or handle special type test data generation rules. Covers DataAnnotations automatic integration, ISpecimenBuilder implementation, priority management. Includes DateTime/numeric range builders, generic design, and fluent extension methods. Keywords: autofixture customization, autofixture customize, autofixture customization, specimen builder, ISpecimenBuilder, RandomDateTimeSequenceGenerator, NumericRangeBuilder, DataAnnotations autofixture, fixture.Customizations, Insert(0), custom builder, NoSpecimen, generic builder

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Using AutoFixture to automatically generate test data basic skill. Used when quickly generating test objects, reducing boilerplate code, and implementing anonymous testing. Covers Fixture.Create, CreateMany, circular reference handling, and xUnit integration. Keywords: autofixture, fixture, auto-generate test data, test data generation, anonymous testing, anonymous testing, fixture.Create, CreateMany, fixture.Build, Create<T>, AutoFixture.Xunit2, OmitOnRecursionBehavior, IFixture, generate test data, generate test data

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Complete guide for code coverage analysis. Use when you need to analyze code coverage, generate coverage reports, or configure CI/CD coverage checks. Covers Coverlet configuration, report generation, metric interpretation, and cyclomatic complexity integration. Includes Fine Code Coverage, VS Code built-in tools, and best practices. Keywords: code coverage, coverage analysis, coverage report, Coverlet, Fine Code Coverage, dotnet-coverage, ReportGenerator, line coverage, branch coverage, cyclomatic complexity, runsettings, cobertura

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Using Bogus to generate realistic fake data specialized skill. Used when generating realistic names, addresses, phone numbers, emails, company info and other test data. Covers Faker class, multi-language support, custom rules, bulk data generation, etc. Keywords: bogus, faker, fake data, fake data, realistic data, realistic data, fake name, fake address, fake email, Faker<T>, RuleFor, Generate, faker.Name, faker.Address, faker.Internet, generate fake data, generate fake data, seed data

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AI-powered wiki generation for code repositories with commands, agents, and skills

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Gather phase context through adaptive questioning before planning. Use --auto to skip interactive questions (the agent picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).

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Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.

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Generate or edit a source-grounded newsletter issue, digest, or briefing from provided or researched sources. Use for weekly/monthly updates, curated links, executive digests, community newsletters, or "turn these sources into a newsletter"; do not use for UI landing pages, marketing campaign design, unsourced news claims, or long-form research reports.

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Design, critique, or specify honest charts and data visualizations from known data and audience needs. Use for chart selection, misleading-chart audits, accessibility, dashboard visuals, or "make this data easier to understand"; do not use for raw data analysis, PPT deck generation, spreadsheet surgery, or fabricated chart data.

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Sets up vector databases for semantic search including Pinecone, Chroma, pgvector, and Qdrant with embedding generation and similarity search. Use when users request "vector database", "semantic search", "embeddings storage", "Pinecone setup", or "similarity search".

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Creates factories and builders for generating consistent, composable test data with realistic values and relationship handling. Use for "test factories", "test data builders", "fixture factories", or "test data generation".

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Generates comprehensive unit tests with AAA pattern (Arrange-Act-Assert), edge cases, error scenarios, and coverage analysis. Creates test files matching source structure with complete test suites. Use for "unit testing", "test generation", "Jest tests", or "test coverage".

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Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".

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Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.

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