「semantic」の検索結果

Adversarially fact-check DOCS.md files against the actual source code, verifying every concrete claim rather than trusting structure checks. Use when the user asks to audit docs, verify documentation accuracy, check whether docs are still true, or on a scheduled documentation review. This is the semantic layer the mechanical checkers cannot cover.

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。

Canonical rules for finding, creating, and updating Shift GitHub issues. Use whenever the user asks to file, create, open, update, triage, or search for an issue, or when substantial work needs an issue before a pull request. Prevents duplicates and defines acceptance criteria and pull-request closure semantics.

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。

Use when a page ranks for a keyword but isn't in the top 3 and you want to know exactly what's missing. The agent compares the page to the top-ranking competitors and produces a specific list of entities, subtopics, and relationships to add.

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 semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of specifications, standards, and project documents.

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。

Map construction data to standard ontologies. Create semantic mappings between different data schemas

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。

Browse and search the OpenConstructionERP cost database: classification tree, SQL and semantic search, autocomplete, certainty badges, and the resource catalog. Use when a user wants to explore cost data without building a BOQ yet.

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。

Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.

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。

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

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。

Convert a light-only site or app to a real dark mode -- semantic token mapping, elevation-based surfaces, recalibrated shadows and imagery -- not a naive inversion. Handles Tailwind, CSS variables, and styled-components, plus the toggle, persistence, and no-flash boot.

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。

Runs multi-source research across GitHub, HN, Reddit, arXiv, and Semantic Scholar. Use when surveying a technical topic across multiple channels.

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。

Analyzes changesets with risk scoring, categorization by type and impact, and release note preparation. Use when extracting insights from raw change data.

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。

Use when finding papers or building a reference list. Searches PubMed, Semantic Scholar and bioRxiv/medRxiv, includes only references verified through an API, and generates BibTeX. Auditing an existing reference list is /verify-refs.

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。

Semantic memory and context - store and retrieve information with embeddings for similarity search. Use for long-term memory, context recall, and knowledge persistence.

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, query, and maintain the qmd-indexed wiki - semantic search, keyword search, re-index after adding pages, check index status.

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。

Use when users ask to 找文献、做文献检索、查论文、查临床试验、核验引用、去重文献、设计 PubMed/MeSH 检索式、追踪上下游引文、解析 DOI/PMID/PMCID/arXiv/OpenAlex/Semantic Scholar/NCT ID， 或导出 RIS、BibTeX、NBIB、ENW；also use for multi-source academic search, citation verification, citation graphs, trial registration search, research workflows, or DeepSeek Harness academic-search MCP 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。

Use when creating, writing, reviewing, annotating, repairing, refactoring, or validating readable Verilog RTL, including synthesizable Verilog-2001 .v files, existing-RTL analysis, semantic comment annotation, testbench scaffold planning, ASIC-quality review, local or remote Vivado/xsim validation, evidence-backed repair, and workflow trace diagnosis.

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。

Coach workers, employees, and individual contributors to turn meetings, transcripts, minutes, and work notes into better execution: infer leader expectations, diagnose previous work, identify next actions, judge delivery readiness, and prepare a high-bandwidth update. Use after meetings, during work, before reviews, or across repeated low-value discussions. Perform semantic review from source evidence.

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。

Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.

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。

Writes and reviews composables for Compose and CMP: the Route/Screen/leaf split, state-read placement and stability, loading/empty/error UX states, LazyColumn lists and grids, animation choice, accessibility and semantics, design-system tokens, CMP Res resources, Coil images, and keyboard/focus. Use when touching @Composable code, recomposition, stability, LazyColumn, animation, shimmer or skeleton, accessibility, theme, colors, Res.string, Coil, focus, or keyboard. Do NOT use for MVI, error tiers, or module graph (compose-architecture), ViewModel or data work (compose-feature, compose-data), Gradle or module work (compose-project), or expect/actual splits (compose-platform).

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。

Analyzes an existing codebase using strategic Domain-Driven Design to discover bounded contexts, surface ubiquitous language and semantic collisions, find places where code boundaries diverge from domain boundaries, and produce an evidence-backed domain and context map. Use when the goal is DDD-specific: bounded context discovery, ubiquitous language analysis, domain model discovery, or mapping contested ownership and responsibility. The entire repository is a valid scope; no module or directory must be named first. Does not assess architectural coupling, cohesion, or technical debt — use architectural-analysis. Does not design service communication, integration patterns, or deployment topology — use architectural-analysis or plan-a-feature. Does not refactor code, diagnose bugs, or review code quality — use refactor, investigate, or code-review.

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。

Create original short videos using the 语义字效｜短语物理逐级升级到整句锁定 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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。

Create original short videos using the 机械语义字场变体｜成年角色让齿轮、弹簧与倒带成为文字 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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。

Create original short videos using the 歌词表演｜稳定主唱锚点与逐句语义升能 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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。

Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed repo.

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。