「semantic」の検索結果

Prepare and risk-check the next rolling-wave slice for implementation. Use when the user wants to continue a rolling-wave project, draft one bounded slice in the main context by default, use a fresh planning author only when context or discovery cost warrants it, use a fresh preparation reviewer when semantic risk or uncertainty warrants independent pressure-testing, decompose parallel implementation chunks where appropriate, identify agent, human, either, or hybrid execution fit, write or update docs/rolling-wave/{project}/slices/NNN-slug.md, and mark that slice ready even when other slices are active.

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Bump the package version and create an annotated git tag. Accepts a semantic version number (1.2.0) or a bump type (patch, minor, major). Does not push — use the publish skill to push. Use as part of a release workflow.

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Expert-level compiler design covering lexical analysis, parsing, semantic analysis, intermediate representations, optimization passes, and code generation.

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Jev (TypeSafe System One) inner loop for ego-browser — one ~0.4 s typed decision per DOM step instead of an LLM turn. Use for multi-step clicking through a semantic page: fill known values into a form, set filters, open a row/card/menu by name, reach a page via nav or site search. Escalates login, payment, free text, canvas and content reading back to you.

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Design and review intuitive, scalable, maintainable HTTP APIs. Use this skill whenever the user wants to design a new REST API, review an existing API or spec, write OpenAPI 3.x definitions, or work with HTTP semantics (GET/POST/PUT/PATCH/DELETE), status codes, idempotency (Idempotency-Key), error envelopes (RFC 7807 problem+json), pagination, filtering, versioning, or API auth (API keys, OAuth2 client credentials, rate limits). Also trigger for "API design", "RESTful", "endpoints", "OpenAPI", "Swagger", "ReDoc", "contract testing", or GraphQL and gRPC design questions.

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Audit datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.

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Author a 3-layer DTCG token system (primitive → semantic → component) with light/dark theming; generate CSS vars + Tailwind colors and lint hardcoded values. Use on design tokens / CSS variables.

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Use when reviewing UI for accessibility — WCAG 2.2 AA, keyboard nav, focus, ARIA, contrast, screen-reader semantics — even on 'is this a11y-OK?' or 'mach das barrierefrei'.

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Escrever código C++ idiomático com recursos modernos, RAII, smart pointers e algoritmos STL. Trata templates, move semantics e otimização de desempenho.

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Mecanismo de busca de similaridade vetorial de alto desempenho para RAG e busca semântica. Use ao construir sistemas RAG em produção que exigem busca de vizinhos mais próximos rápida, busca híbrida com filtragem ou armazenamento vetorial escalável com desempenho impulsionado por Rust.

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Padrões de Retrieval-Augmented Generation incluindo chunking, embeddings, vector stores e otimização de recuperação. Use quando: rag, retrieval augmented, vector search, embeddings, semantic search.

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Banco de dados de embeddings de código aberto para aplicações de IA. Armazene embeddings e metadados, realize buscas vetoriais e full-text, filtre por metadados. API simples com 4 funções. Escala de notebooks para clusters de produção. Use para busca semântica, aplicações RAG ou recuperação de documentos. Melhor para desenvolvimento local e projetos de código aberto.

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Load this skill when building any web feature, reviewing architecture decisions, or evaluating JavaScript dependencies. Under no circumstances build features that break completely when JavaScript is unavailable or fails. Absolutely always start with semantic HTML, layer CSS enhancements, and add JavaScript as the final, optional layer. Prioritize resilience and universal access over cutting-edge features.

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Semantic search over Qdrant Cloud collections using the Python client. Covers vector search, filtered search, prefetch+RRF fusion, group API, recommend API, discovery API, batch queries, scroll, and payload indexing. Use when building search features, adding new query types, or working with qdrant-client.

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Use when generating a single dense technical architecture, reference poster, or system diagram image for a software project. Produces a source-grounded bitmap diagram with topology, primitives, ingest/process flow, core logic, state scopes, tiers/modules, surfaces, runtime cards, and strict semantic color rules.

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Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.

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Semantic audit of the IDD instruction corpus for leaked session context, cross-file contradictions, fresh-memory completability gaps, automation blockers, and restatement-discipline drift. Use on request to audit .github/instructions, the issue-authoring skill bundle, and the installed agent entry files (CLAUDE.md, AGENTS.md, GEMINI.md, .github/copilot-instructions.md). Read-only — never edits files or mutates issues.

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Implement project-consistent UI through page classification, bounded references, semantic tokens, skeleton-first delivery, and responsive screenshot QA. Use for frontend redesigns, dashboards, forms, settings, mobile pages, screenshot recreation, visual polish, or generic-looking generated UI.

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Implement or extend a CPU architecture, processor variant, instruction set, addressing modes, registers, interrupts, bus transactions, disassembly, timing, and processor tests in EMULATORS. Use when adding a processor not yet emulated, deriving a CPU from F6500, FZ80, or another family, filling missing opcodes, correcting instruction semantics or cycles, or creating exhaustive instruction and interrupt tests.

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Verified lookup pack for crouton's schema→CRUD generation domain — the fieldsFile JSON format, the complete field-type catalog with aliases, the naming contract, the exact artifact list one generate run produces, the seed/default-layout pipeline, dialect defaults, and rollback semantics. Use when writing or reviewing a collection schema, when asking "what field types exist / what does `crouton config` actually generate / where did this file name come from / why did I get a pg schema", when a generated file's name or path doesn't match the docs, or when removing/regenerating a collection. Trigger phrases — "what field types are supported", "schema JSON format", "what files does crouton generate", "naming convention for collections", "rollback a collection", "dialect default". The generation WORKFLOW (steps + sign-off gates) lives in the `crouton` skill — this is the reference it doesn't carry.

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Discover, compare, and compose existing open-source GitHub repositories for a user's goal, using GitHub MCP for live discovery and verification plus Context7 semantic retrieval over repository code and official documentation. Use when a user asks for GitHub repo recommendations, open-source alternatives, a multi-repository solution stack, project comparison, or help choosing an implementation to adopt.

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Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, co...

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Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text...

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Configure Azure API Management (APIM) as AI Gateway to secure, observe, control AI models, MCP servers, agents. Helps with rate limiting, semantic caching, content safety, load balancing. USE FOR: AI Gateway, APIM, setup gateway, configure gateway, add gateway, model gateway, MCP server, r...

日本語の概要は準備中です。原文の説明を表示しています。