1,122 件 ・ 関連度順
概要と使いどころ
Shared rules for test runs that drive the running app or run a test target: isolation from concurrent runs, stubs for infrastructure that cannot be stood up, provisioning privileged state, approval before writes to shared external systems, and cleanup of only what the run created. Not typically invoked directly.
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 product leadership toolkit for Head of Product including OKR cascade generation, market analysis, vision setting, and team scaling. Use for strategic planning, goal alignment, competitive analysis, and organizational design.
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。
Complete Product Owner / Product Manager capability — a wiki-style knowledge map of product practice in active software development: the role and its boundaries, strategy cascade (vision → OKRs → roadmap → backlog), continuous discovery, backlog craft (epics, INVEST stories, acceptance criteria), prioritization frameworks (RICE, MoSCoW, Kano, WSJF), sprint delivery, metrics (North Star, AARRR), stakeholder management, and anti-patterns. The PO/PM owns what gets built, in what order, and why — including the end-to-end user flows and user journeys. Use when scoping a product or feature, decomposing an idea into outcomes/epics/stories, prioritizing a backlog, defining an MVP, mapping user journeys, measuring success, or saying no to a stakeholder. Pairs with super-ui-ux-design, which owns how each screen looks and behaves.
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。
Computer vision for bio-image preprocessing, feature detection, real-time microscopy. Color conversion, morphology, contour/blob detection, template matching, optical flow on fluorescence/brightfield. 10-100× faster than pure Python via C++. Use scikit-image for scientific morphometry/regionprops; OpenCV for real-time, video, classical feature extraction.
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 for EPDs by product category, CSI division, or material type — finds EPDs from EC3, program operator registries, and manufacturer sites. Use when the user asks to "find EPDs for...", locate declarations for a material, or source low-carbon product 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。
Register received or authored project documents by confirmed coordinates, preserve their filenames and provenance, and find or verify registered documents. Use for filing a supplied file/package or locating documents by kind, date, source or revision.
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。
Adopt, read, reconcile or revise project FF&E item and schedule records with permanent identities and exact revision pins; preserve native workbook views and recover new artifacts.
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。
Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates. Use when evaluating scope fit, novelty, validity, data, clarity, compliance, advancement, engineering significance, method soundness, experiment sufficiency, baseline fairness, figure/table quality, formatting risks, rejection risk, major revision strategy, pre-submission readiness, or the quality and specificity of reviewer comments that may be generic, careless, contradictory, or possibly AI-generated.
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。
Draft, diagnose, and improve IEEE rebuttals, revision plans, cover letters, response letters, and point-by-point replies using routed reviewer-comment handling. Use when responding to IEEE reviewer or editor comments about novelty, scope, method, experiments, baselines, figures, tables, citations, writing, LaTeX formatting, limitations, compliance, technical correctness, or reviewer comments that appear generic, contradictory, unsupported, careless, or possibly AI-generated.
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。
Evaluates code against Apple's App Store Review Guidelines. Use this skill when reviewing iOS, macOS, tvOS, watchOS, or visionOS app code (Swift, Objective-C, React Native, or Expo) to identify potential App Store rejection issues before submission. Triggers on tasks involving app review preparation, compliance checking, or App Store submission readiness.
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。
Provision a disposable Jurassic Ninja store for the Maestro smoke suite, connect Jetpack to the developer's own WordPress.com test account, create WooCommerce API keys, and write .maestro/.env.local. Use when Maestro setup is missing, when .env.local points at an expired store, or when a clean store is wanted.
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 AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.
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 and analyze key clauses from construction contracts. Identify payment terms, change order procedures, dispute resolution, warranties, and risk allocation provisions.
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 data from construction images using AI Vision. Analyze site photos, scanned documents, drawings.
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。
Track construction submittals through the review process. Manage approvals, revisions, and compliance.
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 construction site photos to track progress, detect safety issues, and compare against BIM models using computer vision.
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。
Track as-built documentation and record drawings. Monitor submission status, manage revisions, and ensure completeness for handover.
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。
Monitor construction progress using computer vision. Analyze site photos and drone imagery to track work completion, detect safety issues, and compare against BIM models.
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。
AI-powered construction defect detection using computer vision. Identify cracks, spalling, corrosion, and other defects in concrete, steel, and building components from images and video.
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。
Previews, provisions, or diagnoses a uv-managed local Python .venv with `databricks environments setup-local`. Use when the user wants to set up or fix one for Databricks Connect, cluster or serverless compute, `--job-task`, or a bundle target, or when setup-local fails.
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。
Review contracts for concerning clauses, extract key terms, compare to standard terms, and flag unusual provisions. Use when user needs contract review, legal document analysis, or agreement evaluation.
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。
Provisions the oracle ML inference daemon with onnxruntime via uv. Use when setting up local ONNX model inference for skill quality evaluation.
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。
Foolbox operating guidance for wrapping vision models, running adversarial attacks, measuring clean and robust accuracy, handling NumPy/PyTorch/TensorFlow/JAX backends, and loading Foolbox-compatible model-zoo 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。
Use Dexbotic to prepare DexData, train and serve vision-language-action policies, evaluate checkpoints, and integrate explicitly external RL or robot backends.
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。