「tables」の検索結果

Assign items to a CLOSED label vocabulary that is too large to put in a prompt — product taxonomies, category hierarchies, tag vocabularies, routing tables, ICD/SIC-style code lists. A cheap model writes the label it thinks the vocabulary would use, and an embedder snaps that writing onto the nearest legal value, so the schema is never transmitted and the output is always in-vocabulary. Use for "classify these into our taxonomy", "tag these against the existing tag list", "map these queries to categories", "the enum is too big to send", or a Literal/enum that hits a provider cap. NOT for a vocabulary that fits in a prompt — structured output measured 0.701 acc@1 there against this pattern's 0.564. NOT for open-ended labelling with no fixed vocabulary, and not for ranked retrieval over documents (bm25).

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。

Debug the AWF firewall by inspecting Docker containers (awf-squid, awf-agent), analyzing Squid access logs, checking iptables rules, and troubleshooting blocked domains or network issues.

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 beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.

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 dark-mode-compatible inline SVG data visualization charts for blog posts. Supports horizontal bar, grouped bar, donut, line, lollipop, area, and radar charts with automatic platform detection (HTML vs JSX/MDX). Enforces chart type diversity, accessible markup (role=img, aria-label), source attribution, and transparent backgrounds. Use whenever the user mentions data visualization, charts, graphs, comparison tables that need to be visualized, or wants to embed inline SVG visualizations in a blog post, even if not invoking blog-write. Use when user says "blog chart", "generate chart", "data visualization", "svg chart", "blog graph", "visualize data", or when the blog-write workflow identifies chart-worthy data points (3+ comparable metrics, trends, before/after 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。

Extract structured company lists from directories with Firecrawl. Use for scraping YC, Crunchbase, Product Hunt, G2, startup directories, category directories, or custom company databases into JSON, CSV, CRM-ready lists, or research tables.

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。

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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 this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use 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。

Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers the explore → prepare projection views → project-compute-write flow, the strict view/column type rules the graph engine requires, exact SQL CALL syntax, and privilege setup in both modes — app-identity grants and execute-as-user / per-user PAT auth (programmatic access token, set_enable_custom_credentials, register_user_role, caller grants). Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-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。

Use when adding character/enemy/game-flow states or NPC behaviour - explicit transition tables instead of flag soup, hierarchical and pushdown machines, behaviour trees per engine, navmesh pathfinding, AI tick budgets, and table-driven tests.

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 while deriving cases - Given/When/Then and the techniques (partitions, boundaries, decision tables, state transitions) that find the cases the criteria do not state

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 PDF content into structured JSON with ComPDF. Use when PDF text, tables, images, and structured content must feed an AI pipeline, application, or system integration.

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。

Database design patterns including schema design, migrations, soft deletes, and Exposed ORM. Use when creating tables, writing migrations, or implementing repositories.

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。

Creates database table with full Kotlin synchronization (SQL migration → Table → Entity → Repository → Tests). Use when adding new database tables or entities.

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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx) or Word templates (.dotx). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file (to download, email or print), use this skill. However, if they ask for a document, page, report, memo, or notes WITHOUT naming a file format and the session offers a dedicated document or page skill or connector, use that instead. Do NOT use for PDFs, spreadsheets, Google Docs, or coding unrelated to document generation.

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 this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use 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。

Designs database schemas, migrations, and data models for PostgreSQL, MySQL, MongoDB, and Redis. Use when planning tables, relationships, indexes, or ORM-backed schema changes.

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。

Builds docxtpl templates, DOCX extraction for RAG, and EAA accessibility checks. Use when templating Word or extracting tables; plain edits and redlines: official docx 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。

Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.

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Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.

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。

Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes. Activates when a user asks about slow pipelines, expensive queries, or performance regressions.

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。

Analyze a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.

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。

Full localization pipeline: scan for hardcoded strings, extract and manage string tables, validate translations, generate translator briefings, run cultural/sensitivity review, manage VO localization, test RTL/platform requirements, enforce string freeze, and report coverage.

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。

Parse PDFs, Office files, images, and HTML into Markdown/structured outputs with MinerU. Use when SciForge or Codex needs document parsing/OCR for scientific papers, supplementary files, PDFs, scanned documents, tables, formulas, or URL/local-file parsing through MinerU standard or Agent lightweight APIs.

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。