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概要と使いどころ
Provides Spring Boot MCP server patterns that create Model Context Protocol servers with Spring AI by defining tool handlers, exposing resources, configuring prompt templates, and setting up transports for AI function calling and tool calling. Use when building MCP servers to extend AI capabilities with Spring's official AI framework, implementing AI tools, custom function calling, or MCP client 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。
Optimize construction resource allocation across activities. Level resources, resolve over-allocations, and balance workload while minimizing schedule impact.
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。
Allocate and track labor resources across project activities. Balance workload, track attendance, and optimize crew assignments.
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 search in the DDC CWICR construction cost database using vector embeddings (BGE-M3, 1024-dim, per-language Qdrant collections). Find similar work items and resources for cost estimation across 8 national bases and 30 markets in 26 languages.
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 resources (labor, materials, equipment) from DDC CWICR database. Calculate resource requirements, productivity metrics, and optimization recommendations.
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, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.
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。
Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit — Node/TypeScript/React) — reach for it first.** Use this skill only when the user asks for a Python backend, extends an existing Python app, or the team is Python-only. Covers OAuth auth, app resources, SQL warehouse and Lakebase connectivity, foundation-model / Vector Search / model-serving APIs (via `databricks-python-sdk`), and deployment via CLI or DABs.
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。
Drive the agentkit CLI (aliases agentkit / ak) to scaffold, build, deploy, and manage agents on Volcengine AgentKit from the terminal — runtimes, knowledge bases, memory collections, tools, harnesses, invocation, SSO auth, sandboxes, and evaluation datasets. Use when a user wants to create/deploy an agent project, call or inspect a deployed runtime, manage AgentKit resources, or resolve a CLI/auth/deploy error. Does NOT handle non-AgentKit deployment, general Docker/k8s operations, Volcengine IAM management, or writing agent application code (use veadk-agent-development for that).
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。
Maintain project state across MULTIPLE conversations over days/weeks. Track tasks, decisions, blockers, resources. Auto-update when project mentioned. Generate status reports and proactive reminders.
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。
Scaffold, build, and package SwiftPM-based macOS apps without an Xcode project. Use when you need a from-scratch macOS app layout, SwiftPM targets/resources, a custom .app bundle assembly script, or signing/notarization/appcast steps outside Xcode.
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 or update a Codex skill with appropriately scoped instructions and any needed supporting resources.
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 the DataSciencePython tutorial/example collection through modern self-contained helpers for Python data-science resources, statsmodels logistic regression, scikit-learn Kaggle-style tabular classifiers, and Twitter JSONL 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。
Use when working with Dagster OSS: assets, jobs, Definitions, config/resources, schedules/sensors, automation, CLI/local development, deployment operations, GraphQL/webserver, Pipes external processes, components/projects, or editing the Dagster repository itself.
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。
Routes tasks for discovering NLP datasets in the CLUEDatasetSearch catalogue, including Chinese NLP classification, QA, matching, NER, generation, translation, corpus, and reading-comprehension resources.
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。
Route Chinese-BERT-wwm model loading, model selection, benchmark data, and troubleshooting workflows for HFL Chinese BERT-family resources.
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。
Operate the Deep Researcher Agent repository for autonomous deep-learning experiments, execution backends, provider/tool dispatch, GPU resources, durable progress, and research-support integrations.
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, generate, write, or scaffold Terraform .tf HCL — resources, modules, providers, variables, outputs.
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。
SST v4 (Ion) expert for managing AWS resources as code with the Pulumi-backed framework.
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。
Automated cleanup of unused AWS resources to reduce costs
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。
Manage EC2 instances, AMIs, and auto-scaling groups. Configure security groups, key pairs, and instance types. Use when deploying compute resources on AWS.
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 Azure resources with ARM templates and Bicep. Create modular deployments and manage dependencies. Use when deploying Azure-native IaC.
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。
Maintain IT asset inventory and configuration management database. Track hardware, software, and cloud resources. Use when managing IT assets.
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 your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
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。
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
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。