クラウド、CI/CD、監視、デプロイ（6,709 件）
概要と使いどころ
arkcli 接入向导(workflow):把某个模型接入到自己的应用/服务的端到端引导 —— 从'我想用某模型'到拿到可调用的 Endpoint(+ 可选示例代码)。当用户说'我想在我的 app/服务里用豆包/某模型''怎么把方舟模型接进来''帮我接入 XX 模型''想正式用上某模型'这类**不含 deploy/部署关键词、但本质是正式接入**的意图时触发。已明确说'部署/创建 endpoint'的直接走 arkcli-deploy;只想试效果/问一句的走 +chat/+gen。反触发：TTS/ASR/语音模型接入不走本向导，只能转 models search 说明 arkcli 当前不支持调用/部署/示例/用量/费用/接入。
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。
arkcli 推理接入点管理与显式 raw CRUD 创建能力。**正向触发：用户明确要求脚本化 / CI / 无护栏 / 原始 raw CRUD 创建 Endpoint 时，必须使用本 skill 的 `arkcli infer endpoint create` 路径，不能切到 `arkcli-deploy`**；模型缺失或只有品牌/家族名时仍留在本 skill，先执行实时有界候选与 0/1/N 澄清，模型未唯一确定前禁止 preview 或创建。本 skill 也负责对**已有** Endpoint 做获取、列表、启动、停止、删除、更新，以及在 NotFound 后用当前完整列表 + 历史 usage 判断 ID 是否不完整或仅有历史记录。普通的『创建/新建/部署一个 endpoint』仍走带产品护栏的 arkcli-deploy（`+deploy`），只有用户明确选择上述原始路径才例外。优先使用产品命令 `arkcli infer endpoint ...`，而不是 Raw API。TTS/ASR/语音模型连 raw create 也不要引导，只能转 models search 说明 arkcli 不支持 Endpoint 创建。
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。
arkcli +deploy：明确指定型号创建接入点也由本 Skill 接管，包括 Retiring 型号；推荐过滤不替代指定目标的实际创建结果。普通创建推理接入点（Endpoint）的统一首选入口。用户说『创建/新建/create 一个 endpoint/接入点』或『部署/上线/deploy 某模型』时优先走这里；**但脚本化 / CI / 无护栏 / 原始 raw CRUD 创建是唯一例外，必须改走 `arkcli-infer-endpoint`，不能由本 skill 截获**。只有不命中该例外的普通创建，才在模型尚未选择、只给品牌/家族名，或当前轮只查询候选时进入本 skill 完成模型澄清；候选要用实时 search 返回的 `name` 与 `primary_version` 组合成可直接传给 `--model` 的完整 ID。对**已有** Endpoint 做获取/列表/启停/更新等全生命周期管理也走 arkcli-infer-endpoint；本 skill 只负责带产品护栏的一键创建。创建成功后会自动把多语言调用示例渲染到 ./ark-examples/<ep-id>/。反触发：TTS/ASR/语音模型不能 +deploy，只能转 models search 说明广场可搜但 arkcli 不支持 Endpoint 创建。
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。
arkcli 模型查询与基础模型服务激活能力：列出、搜索、获取火山公共基础模型详情，以及用户明确要求的开通/激活模型服务（`arkcli models activate`）；Volc 还支持 TTFT/TPOT 性能排名、延迟趋势和输入长度对比。激活已有基础模型服务不等于部署/创建 Endpoint，不得转成 `+deploy`。优先使用产品命令 `arkcli models ...`，而不是直接调用 Raw API。反触发：用户的最终目标是创建 / 部署 Endpoint 时，本 skill 承担有界的只读候选查询，owning skill 由创建路径确定：普通产品创建走 arkcli-deploy；用户显式要求 raw CRUD / CI / 无守卫的 `infer endpoint create` 走 arkcli-infer-endpoint。候选首先执行 `models search ... --size 10 --format json`；成功完整结果直接复用，空结果与捕获缺损按 reference 有界恢复，并把实时返回的 `name` 与非空 `primary_version` 组合成可直接传给 `--model` 的完整 ID，不能拉全量清单、把裸家族名当可部署 ID，或逐候选追加 `models get`。注意：查询/管理账号下自传或精调的自定义模型（`cm-xxx`）走 arkcli-custommodel。
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。
Map the end-to-end service delivery system including frontstage actions, backstage processes, and supporting infrastructure.
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。
Generates a 3-month SEO performance HTML report for any domain using DataForSEO data. Fetches baseline vs current traffic, keyword rankings, top content pages, and competitive landscape, then outputs a report styled with the Infrasity brand design system: #0D0A1A background, #8157F2 purple accent, Instrument Sans + DM Sans + DM Mono typography. Use this skill whenever a user provides a target domain and a list of competitor URLs and asks for an SEO report, performance report, SEO analysis, competitive SEO comparison, traffic report, ranking report, or 3-month SEO summary. Also trigger when the user says "generate SEO report for X vs Y and Z", "create a performance report", "compare my SEO against competitors", or pastes a domain and asks how it's performing versus the market. Always use this skill for SEO report generation — do not attempt to build the report without following this structured data-fetch and HTML generation workflow.
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 Crabbox for ClawBench remote Linux validation. Default to Blacksmith Testbox; includes direct Blacksmith and owned AWS fallback notes when Crabbox 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。
Use when working through architectural flaws documented in a paad/architecture-reviews/ report — selecting which flaws to fix, resuming a partial fix session across multiple sittings, or applying structural changes that need to be tracked back to a report. Not for producing that report — run /agentic-architecture first if there isn't one.
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 through architectural flaws documented in a .reviews/architecture/ report — selecting which flaws to fix, resuming a partial fix session across multiple sittings, or applying structural changes that need to be tracked back to a report. Not for producing that report — run the agentic-architecture skill first if there isn't one.
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 add an in-site feedback loop to a website repo — a floating "提个建议" button where allowlisted visitors submit suggestions that become a GitHub Issue, which GitHub Actions turns into an automatic code change via Claude Code, auto-merges and deploys, and records on a /_feedback dashboard with one-click revert. Triggers — "给网站加个反馈对话框", "提一句话就自动改网站", "装上反馈闭环", "feedback loop", "/wjs-looping-feedback".
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 migrating a WordPress site to a Hugo static site on GitHub Pages from a WXR export (.xml) plus the wp-content/uploads folder — preserving /archives/<id>/ URLs, localizing images, and deploying via GitHub Actions. Triggers — "把 WordPress 迁成 Hugo", "wordpress 转静态站", "migrate WordPress to Hugo", "WXR to Hugo", "publish WordPress to GitHub Pages", "/wjs-converting-wp-to-hugo".
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 ArvanCloud (arvancloud.ir) through its REST APIs, including CDN and DNS records, domains, cache purge, WAF and rate limits, Cloud Server (IaaS v3, v1 and the undocumented v2 backups), Object Storage, Edge Computing, Cloud Container, VOD, Live and Video Ads, plus Let's Encrypt DNS-01 certificates via acme.sh dns_arvan. Use when the user wants to list, create, change or delete anything on ArvanCloud, take an account inventory, find out which account a key belongs to, check quota or usage, or debug an ArvanCloud API error. Also trigger on hosts like napi.arvancloud.ir, ecc.{region}.arvanapis.ir, storage.arvanapis.ir, dejban.arvancloud.ir, an "Apikey" Authorization header, the dns_arvan plugin, or one of the user's ArvanCloud-hosted domains.
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。
Set up or tune any dev machine, fresh or drifted, on macOS, Linux, or Windows: report what's missing, install only that, then fix PATH, duplicate runtimes, and shell config. Don't use for Dockerfiles, CI images, or single package installs.
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。
Generate cross-platform install scripts for any software or library — a standalone install.sh runnable via a curl/wget one-liner with OS, arch, and package manager detection. Don't use for Dockerfiles, CI/CD pipelines, or one-off shell scripts.
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 and debug Python applications using AgentScope 2.x. Consult this skill for AgentScope APIs, agent tools, multi-agent orchestration, and agent service deployment.
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。
Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.
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。
Applies the engineering and research philosophies of Jeff Dean, Chief Scientist at Google DeepMind and Google Research. Reach for this skill whenever you are designing large-scale distributed systems, optimizing latency and energy efficiency, or making architectural decisions about machine learning infrastructure. It should trigger automatically for topics involving hardware-ML co-design, model distillation, sparse activation, massively multi-task models, or scaling systems by 5x to 10x. Use this skill to evaluate system bottlenecks, transition from specialized to unified models, and optimize experimental velocity. Apply his mental models to avoid premature 100x scaling and to treat AI models as reasoning engines rather than memorization databases.
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 this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.
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。
Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.
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。
Suede Thought Graph shipping search for a multi-file repo change. Use when competing implementation plans need one evidence-gated selection before any build. Halts on hazards, collisions, budget exhaustion, or no safe winner. Reads production; never deploys. NOT FOR: bulk independent work (use a separate private worker-fleet pass); findings-only diff review (use suede-code-review); CI or branch-protection wiring (use suede-ci-gate); copy-only shipping (use suede-ship-copy).
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。
Axone deployment workflows with cargo-make, cw-orch, and Abstract. Use when publishing modules, installing them on accounts, running local chain tasks, or inspecting deployments.
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 a codebase and generate or update its README.md according to best practices. The skill performs static analysis of the project structure, dependencies, scripts, and existing documentation, then produces a comprehensive, accurate README. **Triggers — use this skill when:** - User asks to "review", "update", "improve", or "generate" a README - User says "create a README for this project" - User mentions "document this repo", "add documentation" - User asks to "fix my README" or "make my README better" - User provides a codebase and asks for documentation help **Covers:** Any project type — Node.js, Python, Rust, Go, Java, Ruby, PHP, monorepos, static sites, CLI tools, libraries, APIs, Docker-based projects, and more. Works with both new READMEs (from scratch) and existing ones (update/improve).
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。
Structured planning mode for AI agents working on coding and development tasks. Produces a comprehensive plan BEFORE any code is written or changed, including task decomposition, architecture decisions, risk assessment, and approval gates. Use this skill whenever the user says "/plan", "plan mode", "plan first", "think before coding", "make a plan", or asks the agent to plan before executing. Also trigger when the user describes a complex multi-step development task and would clearly benefit from structured planning before implementation — especially for tasks involving new features, refactors, migrations, infrastructure changes, or multi-file edits. When in doubt, plan. A few minutes of planning prevents hours of rework.
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。
OpenClaw usage expert: Helps you install, deploy, configure, and use OpenClaw personal AI assistant. Can diagnose issues, create bots, execute automated tasks, etc. Use when users need to install OpenClaw, configure Gateway, set up Channels, create Agents, troubleshoot issues, or perform OpenClaw-related 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。