「vision」の検索結果

Infrastructure engineer — cloud services, IaC, networking, cost optimization. Use when asked to "provision infra", "write Terraform", "cut cloud costs", or "design the network".

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Build onboarding playbook - day 1 through week 4 checklist, access provisioning, context transfer, and success milestones. Use when asked to "build an onboarding process", "how do we onboard new hires", or "reduce time to productivity for new joiners".

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 production-grade infrastructure as code for a service or project. Use when asked to "set up infra", "provision infrastructure", "create cloud resources", "IaC for this project", "terraform for this", or "deploy this service".

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Strategic narrative — write a standalone strategy memo that frames product direction, bets, and rationale for a planning horizon. Use when asked to "write a strategy doc", "product vision", "strategic narrative", "company strategy memo", "planning memo", or "explain our product direction".

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。

Expert guide for WebXR spatial computing, Web-based Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) using Babylon.js and Three.js. Covers Apple Vision Pro, Meta Quest 3, hand tracking, and hit-testing / Panduan ahli WebXR spatial computing (VR/AR/MR).

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Naming and classifying organisms through binomial nomenclature, the Linnaean hierarchy, type specimens, and the rules governing taxonomic authority and revision. Covers the structure of a scientific name, the ranks from domain to subspecies, the codes (ICZN, ICN, ICNP), and the modern phylogenetic refinements that reshape the classical system. Use when the task is to place a known organism in its formal hierarchy or to reason about how names change over time.

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Provides Infrastructure as Code best practices for Terraform, Pulumi, CloudFormation, and OpenTofu. Use when provisioning infrastructure, writing IaC modules, managing cloud resources, scanning for misconfigurations, or when user mentions 'terraform', 'pulumi', 'cloudformation', 'IaC', 'opentofu', 'infrastructure', 'tfsec', 'checkov', 'drift'.

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The pedagogy of feeding — how to talk about food with children, what the Division of Responsibility model says, age-appropriate autonomy in eating, how to handle picky eating without creating disordered eating, and how to teach nutrition concepts to learners at different levels without either moralizing or oversimplifying. Use when a question is about raising, teaching, or advising a child or learner on eating, or when planning curriculum or parent guidance.

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Economic analysis of government intervention -- taxation (incidence, efficiency, optimal design), regulation (cost-benefit, market failure correction), externalities (Pigouvian taxation, cap-and-trade, Coasian bargaining), and public goods provision (non-rivalry, non-excludability, free-rider problem). Covers welfare analysis of policy interventions, government failure, and the institutional context of policy-making. Use when evaluating policy proposals, analyzing tax effects, assessing regulatory design, or reasoning about the appropriate scope of government action.

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Package conversation research into a GSD-ready mission package. Produces a three-stage Vision → Research → Mission pipeline as a LaTeX PDF following GSD/NASA SE methodology, designed to be handed to gsd-skill-creator for execution. Use this skill when the user has been discussing, researching, or brainstorming a topic and then asks to turn it into a research mission, research pack, mission package, or says 'package this as a mission', 'make this a research pack', 'turn this into a mission for skill-creator', 'create a research mission from this', or 'use the research mission skill'. The skill harvests findings, sources, and structure from the current conversation and any prior research, then produces the complete pipeline document. Also trigger if the user asks to 'create a research mission on [topic]' cold — in that case, conduct web research first, then package.

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Interrupt controller converting polled to proactive agent execution. Per-runtime strategies, configurable thresholds, Deacon heartbeat supervision. Fights LLM passivity bias.

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OpenStack capacity planning operations skill for resource planning, quota management, and scaling decisions. Covers compute capacity (allocation ratios, vCPU/RAM utilization, host aggregates, availability zones), storage capacity (Cinder pool sizing, thin provisioning, Glance storage, Swift rings), network capacity (floating IP pools, port quotas, subnet sizing), project quota management (templates for small/medium/large profiles), flavor sizing strategy, utilization analysis with placement service, growth forecasting from historical metrics, and right-sizing recommendations for underutilized resources.

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OpenStack monitoring operations skill for deploying, configuring, and operating the cloud health monitoring stack. Covers Prometheus metric collection and scrape targets, Grafana dashboard provisioning and visualization, Alertmanager notification channels and routing, alerting rules for service health and resource exhaustion, service endpoint health checks, log aggregation strategies, SLA tracking with availability and response time percentiles, and capacity trend analysis from historical metrics. Use when deploying monitoring via Kolla-Ansible, configuring alert thresholds, troubleshooting blank dashboards, tuning noisy alerts, or analyzing cloud performance trends.

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 text visible in an image (OCR) with a local vision LLM. Wraps kuzco's tool_llm_image_extract_text() ellmer tool. Use when the task needs reading text from screenshots, documents, signs, labels, or any image containing writing.

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。

Recognize and locate instances of an object in an image with a local vision LLM. Wraps kuzco's tool_llm_image_recognition() ellmer tool. Use when the task needs finding, counting, or locating specific objects (faces, cars, animals) in an image.

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Generate accessibility alt text for an image with a local vision LLM. Wraps kuzco's tool_llm_image_alt_text() ellmer tool. Use when the task needs a short textual description of an image, e.g. for accessibility, captions, or image indexing.

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 the sentiment or mood conveyed by an image with a local vision LLM. Wraps kuzco's tool_llm_image_sentiment() ellmer tool. Use when the task needs the emotional tone of an image, e.g. for content moderation, marketing, or curation.

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。

Classify an image and describe its contents with a local vision LLM. Wraps kuzco's tool_llm_image_classification() ellmer tool. Use when the task needs image classification, object identification, or a structured description of what an image contains.

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。

Custom board bringup for Zephyr RTOS using Hardware Model v2 (HWMv2). Covers directory structure, board.yml metadata, core configuration files (Kconfig, defconfig, CMake), and revision management. Trigger when creating new board definitions or porting Zephyr to custom hardware.

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。

Launches and supervises long-running commands — solves, workflows, downloads, builds — detached with a log, PID and exit sentinel, then tells stuck from slow and kills verifiably. Use before running anything that may exceed a minute, for nohup or background launches, and when a run hangs, shows no output, or timed out.

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漫画の場面で狙う笑い・魅力・感情・関係・展開の効果を監修する。字コンテ・ネームの表現相談とPNGレビューで、場面に必要なテーマの知識を選び、人物や設定を保つ改善案を比較するときに使う。

Deploy Coolify self-hosted PaaS for application hosting. Covers VM provisioning, installation, GitHub integration, and application deployment with auto-SSL.

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。

Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.

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Manages the research/ knowledge base of verified tool and library research entries via knowledge-explorer.py. Commands — list (browse by category or SDLC layer), fetch-github (draft entry from GitHub repo), add (validate and route to category dir), update-append (append dated revision), generate-descriptions (repair missing or low-quality descriptions), migrate (convert inline-header entries to frontmatter). Use when browsing KB topics, adding or updating research entries, fetching GitHub repo metadata, generating descriptions in parallel via Haiku subagents, or migrating old-format entries to skill-spec frontmatter.

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。