「forms」の検索結果

Geospatial vector analysis extending pandas. Read/write spatial formats (Shapefile, GeoJSON, GeoPackage, Parquet, PostGIS), CRS handling, geometric ops (buffer, simplify, centroid, affine), spatial analysis (joins, overlays, dissolve, clipping, distance), visualization (choropleth, interactive maps, basemaps). Use for spatial joins, overlays, CRS transforms, area/distance, maps.

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。

Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.

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 best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.

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。

Provides patterns and code examples for building Next.js 16+ applications with App Router architecture. Use when creating projects with App Router, implementing Server Components and Client Components ("use client"), creating Server Actions for forms, building Route Handlers (route.ts), configuring caching with "use cache" directive (cacheLife, cacheTag), setting up parallel routes (`@slot`) or intercepting routes, migrating to proxy.ts, or working with App Router file conventions (layout.tsx, page.tsx, loading.tsx, error.tsx).

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。

Provides complete shadcn/ui component library patterns including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building forms with React Hook Form and Zod, customizing themes with Tailwind CSS, or implementing UI patterns like buttons, dialogs, dropdowns, tables, and complex form layouts.

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。

Provides automated documentation updates by analyzing git changes between the current branch and the last release tag. Performs git diff analysis to identify modifications, then updates README.md, CHANGELOG.md following Keep a Changelog standard, and discovers documentation folders for contextual updates. Use when preparing a release, maintaining documentation sync, or before creating a pull request. Triggers on "update docs", "update changelog", "sync documentation", "update readme", "prepare release documentation".

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, implement, audit, or review Shift user interfaces and shared UI components. Use for React components, Base UI primitives, Tailwind styling or theme tokens, Figma/reference matching, accessibility, icon-only actions, tooltips, menus, popovers, dialogs, forms, layout, and visible UI 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。

When the user wants to research customer pain points, complaints, or sentiment using review platforms like Trustpilot, G2, Capterra, or app stores. Also use when the user mentions "what are users saying", "competitor reviews", "pain points", or "voice of customer research".

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。

PDF processing for construction documents: RFIs, submittals, specifications, drawing packages. Extract data, merge packages, fill forms.

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。

Process construction payment applications. Validate schedule of values, calculate retainage, track billing status, and generate G702/G703 forms.

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。

Assess company readiness for construction industry uberization. Analyze data transparency, process automation, and competitive positioning against open data platforms.

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。

Answers business questions about the user's own spreadsheet or data export (CSV, TSV, XLSX from a CRM, Shopify, Stripe, QuickBooks, ad platforms, HR or payroll systems) correctly and auditably. Profiles every file first (grain, duplicate keys, embedded Grand Total rows, text-stored numbers, mixed currencies, UTC timestamps, Excel serial dates, hidden rows), states the metric definition used, computes every number in SQL or pandas instead of mental math, checks joins for fan-out, reconciles to a known total, and returns the query, filters, row counts, and rows behind the answer. Use this whenever the user says "analyze this spreadsheet", "how many...", "what's the total in this export", "which customers...", "pivot this", "revenue by month", "top 10", "what's our churn/MRR/AOV", or asks any question about their data, CSV, or Excel file, even a quick one. Also use when they ask to change values in a data file.

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。

Performs a deep code review of files, modules, a diff, or a branch - finding security vulnerabilities (mapped to OWASP Top 10:2025), correctness bugs, performance problems, and maintainability issues - and returns severity-ranked findings with evidence and concrete fixes. Use when the user asks to review, audit, or sanity-check code, asks "is this safe", "what's wrong with this", "find bugs", or wants a security or performance pass before shipping. For posting line comments on a GitHub pull request, use git-pr-reviewer.

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。

Master skill that transforms ANY content into 8+ formats: slides, infographic, video script, podcast, social posts, email series, flashcards, quiz, one-pager, interactive game.

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。

Decides hand-vs-compiler for loop transforms (unrolling, SIMD, fusion, branchless). Use when reviewing/authoring a hot loop or tempted to hand-optimize one.

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。

Transforms project briefs into testable specifications with user stories and acceptance criteria. Use after brainstorming, before planning.

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。

Applies microkernel architecture with minimal core and plugin extensibility. Use when building platforms where third parties extend core functionality.

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 rendering a Markdown document (English or Korean) such as a proposal, IRB cover letter, handout or reference table to PDF via pandoc and xelatex, with auto-fitted table widths and CJK fonts. Not for manuscripts with a bibliography (/manage-refs) or Word forms.

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。

Collect and research materials for X (Twitter) content creation using multi-round web search strategy. Use when user wants to gather trending topics, research subjects for X posts, or mentions "collect materials", "research topic", "find content for X", "x-collect". Performs 4-round deep research mimicking human research workflow.

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 FFCV to convert datasets into .beton files, build fast PyTorch loader pipelines, handle image and custom fields/transforms, and tune cache, traversal, and throughput behavior.

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。

Guides Fiona workflows for GDAL-backed vector data I/O, GeoJSON-like features and schemas, CRS transforms, local virtual files, cloud-session boundaries, and the fio CLI.

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 DeepMind dm-haiku as a JAX neural-network library for transforms, modules, state/RNG, layers, advanced JAX interop, and optional Flax interop.

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 someone wants to build, refine, or audit their personal brand positioning across professional platforms. Triggers on "personal brand", "brand positioning", "brand voice", "how should I position myself", "professional identity", "LinkedIn presence", "build my brand".

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。