「environment」の検索結果

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

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 checking deployment health, investigating errors, reading logs, or working with Tiltfiles. Queries Tilt resource status, logs, and manages dev environments.

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 the user wants to set up or troubleshoot a LaTeX environment, choose between biber and bibtex, install packages for a specific venue template, or configure compilation. Triggers on phrases like "setup latex", "biber vs bibtex", "latex compilation error", "install latex packages", "venue template", or "texlive 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。

Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.

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。

Configure Claude Code sandbox network isolation with trusted domains, custom access policies, and environment variables

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 and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".

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。

Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.

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 durable execution to a TypeScript project — building retry-safe webhook handlers, background jobs that survive crashes, scheduled tasks, or long-running workflows that outlive a single request. Covers Inngest SDK installation, client config, environment variables, serve endpoints (Next.js, Express, Hono, Fastify), connect-as-worker mode, and the local dev server.

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 scRNA-seq cell type annotation via pre-trained logistic regression. 45+ models: immune, gut, lung, brain, fetal, cancer microenvironments. Input normalized AnnData; outputs per-cell labels, majority-vote cluster labels, confidence scores. Use for fast, reference-backed annotation without manual marker inspection.

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 to deploy ECS tasks and services with GitHub Actions CI/CD. Use when building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Supports ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.

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 for unit testing `@ConfigurationProperties` classes with `@ConfigurationPropertiesTest`. Validates property binding, tests validation constraints, verifies default values, checks type conversions, and mocks property sources for Spring Boot configuration properties. Use when testing application configuration binding, validating YAML or application.properties files, verifying environment-specific settings, or testing nested property structures.

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 comprehensive patterns for deploying Next.js applications to production. Use when configuring Docker containers, setting up GitHub Actions CI/CD pipelines, managing environment variables, implementing preview deployments, or setting up monitoring and logging for Next.js applications. Covers standalone output, multi-stage Docker builds, health checks, OpenTelemetry instrumentation, and production best practices.

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 starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed seeds, and immutable raw 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。

Databricks AI Runtime, the `databricks air` CLI commands for submitting and managing GPU training workloads on Databricks serverless compute. Use for: writing and submitting `databricks air` workload YAML, passing hyperparameters and secrets, checking run status, listing/cancelling runs, streaming a run's logs and watching its progress, custom Docker image setup, and environment configuration.

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。

One-time environment setup for new team members

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。

Rebuild the dev environment: uv, Python tiers, pins, traps. Use when onboarding or toolchain breaks. Do not use for daily commands; use night-market-operations.

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 skill fails for a missing tool or the environment needs checking. Diagnoses Python, R, Node, Claude Code, Git, Zotero and configured MCP servers and prints a pass/fail table with links to the setup docs. Read-only; installs nothing.

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 DI-engine users to the right workflow for CLI/config launches, serial and framework-based RL pipelines, and environment 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。

Guide ROS/Gazebo Velodyne mobile-robot navigation with the DRL-robot-navigation TD3 implementation, including simulator setup, environment contracts, bounded training, checkpoints, and policy 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。

Use DreamerV3 for world-model reinforcement learning training, embodied environment dataflow, JAX model internals, result operations, and troubleshooting.

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_control for MuJoCo simulation, Control Suite environments, PyMJCF models, Composer tasks, rendering, and high-level locomotion/manipulation workflows.

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 Any4LeRobot dataset conversions, LeRobot-to-RLDS export, and LeRobot v1.6-v3.0 format migrations with schema validation, version-aware environments, and safe publication boundaries.

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。

Prepare the local environment for the Maestro smoke-test suite — verify tooling, select a device, collect the APK if needed, validate the .env file by variable name only, then hand the user the exact lab-store CLI command to run or run it on request.

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。