「machine」の検索結果

AWS EC2 virtual machine management — instances, security groups, key pairs, AMIs, EBS volumes, Auto Scaling Groups, Spot Instances, Session Manager, placement groups, and instance lifecycle automation. Trigger on ANY of these, even when EC2 isn't named explicitly: - Launching or provisioning: "spin up a server", "create a VM", "new instance", "run-instances", mention of instance types (t3, m5, c5, r6, g5, p4d, t4g, c7g, etc.) - SSH / connectivity problems: "connection refused", "connection timed out", "permission denied publickey", "can't connect to my instance", "SSH not working" - Instance management: resize, stop, start, terminate, reboot, change instance type - Cost optimization: stop dev instances overnight, save money on EC2, spot vs on-demand, reserved instances - Auto Scaling: ASG, launch template, mixed instances policy, scale to zero, scheduled scaling - Spot Instances: spot fleet, spot interruption, capacity-optimized, price-capacity-optimized - AMIs and backups: create image, custom AMI, EBS snapshot, DLM lifecycle policy, copy AMI - Monitoring: EC2 CPU utilization, CloudWatch metrics for instance, instance status checks, console output - Access methods: Session Manager, EC2 Instance Connect, bastion host, port forwarding - Security: IMDSv2, instance metadata, IAM role on instance, security group rules - User data and bootstrap scripts, cloud-init

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。

AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or debugging executions.

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 Azure Virtual Machines and scale sets. Configure availability sets and managed disks. Use when deploying compute resources on Azure.

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 reproducible development environments with Dev Containers, Nix flakes, and Devbox for consistent toolchains across teams. Use when onboarding developers, standardizing build environments, or eliminating "works on my machine" problems.

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。

Import Claude Code or Codex history and move complete CCAM datasets between machines. Use when rescanning provider history, importing a copied directory, uploading JSONL or archives, exporting a backup, restoring it idempotently, or verifying that tokens, workflows, runs, rules, and pricing survived.

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 and troubleshoot CCAM Remote Data Sources that collect Claude Code and Codex history over SSH. Use when adding, editing, testing, syncing, or removing a remote machine, verifying provider paths, or deciding whether to retain or purge imported sessions.

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。

Inspect a mathematical-modeling workspace, evaluate lean or submission gates per subquestion, update machine-readable manifests, classify change impact, and route one next action without duplicating downstream work.

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Design and run risk-targeted robustness, sensitivity, error, and baseline checks for an approved mathematical model, emitting compact machine evidence in lean mode and a final report in submission mode.

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Translate, transcreate, review, or maintain multilingual product and marketing content, including source locking, glossary decisions, language style, machine-assisted workflows, legal-content safeguards, QA, and source-change synchronization. Use localization-strategy for market scope, locale architecture, rollout, and production release planning.

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Drive the Skills Manager CLI (`skm`) to initialize the hub, adopt unmanaged skills, list/enable/disable skills per AI tool, and doctor/fix symlink sync. Use whenever the user or an agent needs to manage skills from a terminal, SSH session, CI job, or headless machine; when a skill is missing in Claude Code, Codex, Cursor, Gemini, OpenCode, or any other supported tool; when asked to run skm / Skills Manager CLI; or when setting up Skills Manager without the GUI. Do not use for `npx skills` / skills.sh search (different CLI), for writing SKILL.md content (skill-creator), or for marketplace browse/install (not in skm).

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Use when a Unity 6.3 task involves character animation or cameras: Mixamo or mocap humanoid import and retargeting, Animator Controllers, blend trees, layers and avatar masks, root motion, foot sliding, IK and Animation Rigging, Playables, Timeline cutscenes, custom tracks and markers, Cinemachine 3 cameras, camera jitter, flipping blends or cameras hitting walls; or when clips import with no animation, a character T-poses, an idle drifts, feet slide or the head misses its aim target.

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Use when building gameplay systems in Godot 4.7: enemy AI that patrols, chases and attacks, state machines, behavior trees (LimboAI), NavigationAgent3D pathfinding and avoidance for 100 to 1000 enemies, 'agents stack up' or 'path is empty', hitbox and hurtbox combat, fast bullets going through walls, save and load, inventory, quests, dialogue (Dialogue Manager), input remapping, procedural dungeons, or measuring agent counts and frame time headless.

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Use when building or debugging Unity gameplay systems: enemy AI that patrols, chases and attacks, NavMesh baking and agents (AI Navigation 2), feet sliding on agents, state machines or behavior trees, physics projectiles that tunnel, the physics spiral, layers and the collision matrix, CharacterController vs Rigidbody characters, object pooling, 'hundreds of enemies', DOTS, Burst or Jobs decisions, Netcode for GameObjects multiplayer, audio mixers, snapshots, volume sliders and 3D combat sounds.

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 UE5 task involves characters in motion: "import FBX from Maya" with a skeleton, "retarget animations", IK Rig, IK Retargeter, feet sinking or floating after retarget, mocap cleanup, Motion Matching, Pose Search, Choosers, GASP, state machine vs motion matching, root motion, offset root bone, foot IK, Control Rig, Animation Blueprint cost, "animation is expensive", budget allocator, URO, MetaHuman LODs, ML Deformer, cloth.

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 animating characters or scenes in Godot 4.7: AnimationPlayer clips and RESET, AnimationTree state machines and blend spaces built in code, Mixamo or glTF import, loop settings, BoneMap retargeting and shared animation libraries, root motion, foot sliding, foot IK with TwoBoneIK3D or custom SkeletonModifier3D, tweens, SpringArm3D cameras, cutscenes; or when a character T-poses, slides, floats, freezes mid-blend or a transition never fires.

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 modeling hard-surface objects in Blender (sci-fi panels, props, weapons, vehicles, robots, machined or product parts) with booleans and cutters, bevel modifiers, weighted normals, or subdivision with support loops or creases. Also when shading is broken (smears on flat faces, stretching near a cut, pinching), a bevel shrinks or vanishes after a boolean, a boolean empties the mesh or leaves holes, choosing n-gons vs quads, or making a game-ready mid-poly.

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 generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.

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。

Virtual machine management with KubeVirt on Kubernetes. Use when creating, managing, or troubleshooting VMs running on Kubernetes clusters.

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。

Quantum machine learning and differentiable quantum computing

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。

Genomic interval machine learning for regulatory element analysis

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Build workflows with AWS Step Functions state machines using the JSONata query language. Covers Amazon States Language (ASL) structure, state types, variables, data transformation, error handling, AWS service integration, and migrating from the JSONPath to the JSONata query language.

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Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless applications.

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Multi-agent source security audit with a coverage ledger, independently verified findings, and machine-checked records. Use when asked to audit a codebase, find vulnerabilities, or run a source-level pen test.

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。

Build Amazon Machine Images (AMIs) with Packer using the amazon-ebs builder. Use when creating custom AMIs for EC2 instances.

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。