「arc」の検索結果

Optimize similarity search — ANN index tuning, hybrid search, reranking, query expansion. Use when asked to "improve similarity search", "tune the ANN index", or "add hybrid search".

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。

Conducts a systematic related-work / literature-survey / state-of-the-art review for a research question by defining survey dimensions, searching each axis, building a taxonomy of prior work, identifying the gap, and producing a positioning narrative for a paper's Related Work section. Goes beyond a flat paper list to deliver structured analysis. Use when the user is starting a new research project and needs to map the landscape, asks "what's been done on X?" or "how does my idea compare to existing work?", needs to write or revise a Related Work / Background / Prior Art section, wants to identify a research gap or position their contribution, or asks to build a taxonomy of approaches in a research area.

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Purpose: Standardize how stakpak designs and optimizes AWS architectures. Scope: Greenfield: design new infrastructure. Brownfield: analyze existing architectures and propose improvements.

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。

Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the backlog.

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。

Implement Algolia search UIs in Nuxt 3 apps using @atoms-studio/nuxt-swiftsearch — an SSR-first, fully typed alternative to vue-instantsearch.

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。

Deprecated alias. This skill was renamed to `deepline-research`. Use when a user or script still invokes `/deepline-pre-research`: immediately load and follow the `deepline-research` skill instead. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.

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。

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

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。

Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.

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。

REQUIRED for end-user customization of Linux desktop, window manager, or system config. Use when editing ~/.config/hypr/, ~/.config/omarchy/, ~/.config/alacritty/, ~/.config/foot/, ~/.config/kitty/, or ~/.config/ghostty/. Triggers: Hyprland, window rules, animations, keybindings, monitors, gaps, borders, blur, opacity, omarchy-shell, bar, terminal config, themes, background, night light, idle, lock screen, screenshots, reminders, layer rules, workspace settings, display config, and user-facing omarchy commands. Excludes Omarchy source development through `omarchy dev link` workflows.

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。

Build an AEO-first topical map optimized for AI search citation — entity clusters, query fan-out coverage, information gain scoring, and multi-platform distribution. Produces entity map, content node architecture, schema blueprint, and 90-day publishing calendar. Use when "topical map", "content architecture", "site structure", "topic clusters", "pillar content plan", "AEO map", "AI search architecture", "entity map", "what content should we build", or any request to plan a site's topical structure for AI search visibility.

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。

Search academic papers, build literature reviews, and synthesize research findings — combines Exa MCP (research_paper category, arxiv filtering) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.

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。

Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews, committing code, creating PRs, loading coding guidelines (TypeScript, Python, TDD, golden testing, Convex, monorepo patterns), code cleanup, research briefs, architecture docs, agent handoffs, and checking out third-party library source code. Invoke when user mentions: tbd, beads, bd, shortcuts, issues, bugs, tasks, features, epics, todo, tracking, specs, planning, implementation, validation, guidelines, templates, commit, PR, pull request, code review, testing, TDD, test-driven, golden testing, snapshot testing, TypeScript, Python, Convex, monorepo, cleanup, dead code, refactor, handoff, research, architecture, labels, search, checkout library, source code review, or any workflow shortcut.

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。

Deploy a self-hosted SearXNG meta search engine via Docker Compose. Covers settings.yml configuration, engine selection, result proxying, Nginx frontend, persistence, and updates. Use when setting up a private search engine without tracking, aggregating results from multiple providers, running a shared search instance for a team or organisation, or replacing reliance on a single search provider.

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。

Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after $aif setup.

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。

Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after /aif setup.

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。

Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after $aif setup.

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。

Strategic keyword research powered by web search and brand context. Use this skill whenever the user mentions keywords, keyword research, SEO topics, content topics, 'what should I write about', content strategy, blog ideas, search traffic, or content planning. Also trigger when the user wants to plan what content to create, when existing content isn't attracting search traffic, when any skill needs keyword-plan.md but it doesn't exist, or when the user asks about SEO in the context of content creation. Even casual mentions like 'I need blog post ideas' or 'what topics should I cover' warrant this skill. 8-phase process from seed to content brief.

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。

OpenSearch provider for obz. Supports log search and trace operations using Lucene-based query syntax. Requires --index flag. This skill should be used when the user mentions "OpenSearch", "obz -p os", or needs to search logs or traces from an OpenSearch cluster.

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。

Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews, committing code, creating PRs, loading coding guidelines (TypeScript, Python, TDD, golden testing, Convex, monorepo patterns), code cleanup, research briefs, architecture docs, agent handoffs, and checking out third-party library source code. Invoke when user mentions: tbd, beads, bd, shortcuts, issues, bugs, tasks, features, epics, todo, tracking, specs, planning, implementation, validation, guidelines, templates, commit, PR, pull request, code review, testing, TDD, test-driven, golden testing, snapshot testing, TypeScript, Python, Convex, monorepo, cleanup, dead code, refactor, handoff, research, architecture, labels, search, checkout library, source code review, or any workflow shortcut.

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。

行业调研——researcher CLI + 多 Agent 对抗式研究引擎。输入一个行业/赛道/商业机会的模糊需求， 输出一份有据可依、经过证据校验和红蓝对抗检验的战略调研报告。内置国民经济行业分类映射、 MECE/PESTLE/波特五力等咨询框架、事前验尸法和黑格尔辩证法合题引擎。 支持精简/标准/深度三种报告深度。 触发方式：/industry-research、「行业调研」、「行业分析」、「赛道研究」、「市场调研」 Use when the user asks for industry research, sector analysis, market study, competitive landscape analysis, investment thesis research, or any request involving structured industry investigation. Also trigger when user mentions 调研报告, 行业研究, 赛道分析, 商业机会分析, 投资逻辑梳理, or similar phrases. Even casual requests like "帮我看看 XX行业怎么样" or "XX赛道值不值得做" should trigger this skill.

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。

Meilisearch search engine patterns -- client setup, indexing, search, filtering, facets, geo search, multi-tenancy, task management

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。

This skill provides guidance for using Brave Search MCP to search the web. Use when searching for current information, news, articles, local businesses, or any web content. Supports both general web searches and location-based local searches.

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。

Opt-in DI architecture using Reflex for Unity 6+. Covers container setup, scoping, injection, command pattern, update management, and class taxonomy. Use when ProjectConfig.yaml -> architecture_pattern is "di-first", or when the user asks about dependency injection, inversion of control, service architecture, or testable game code. Triggers on "set up DI", "add dependency injection", "create a service", "wire up dependencies", "make this testable", "decouple these systems", "add a command pattern", "cross-feature communication", or architecture discussions involving testability, decoupling, and service layers. Only activates when ProjectConfig.yaml -> architecture_pattern is "di-first". For simpler projects, use uw-scriptable-object-arch instead.

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。

Apply source-aware mechanical-engineering judgment to research, analysis, coding, writing, teaching, research identity, and release work. Use for thermal-fluid systems, heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, piping, multiphase flow, experiments, correlations, CFD, reduced-order models, AI/ML, uncertainty, engineering datasets, literature reviews, citations, manuscripts, reviewer revisions, Overleaf packages, figures, proposals, research software, reproducibility, public releases, engineering teaching materials, or a research-project logo and visual identity.

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。