「dev tool」の検索結果

Daytona development environment overview. Use when the user asks about Daytona setup, Daytona toolbox, dev environment, noVNC, CDP, server sandbox, secrets volume, Electron sandbox, standalone Chrome, validation, or artifacts volume.

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This skill helps users extract GitHub repository project details and contributor contact information using keywords, stars, and update dates. Agent should proactively apply this skill when users express needs like search for GitHub projects by keywords, find top open-source contributors in specific domains, extract developer contacts from GitHub repositories, discover trending repositories with high stars, gather contributor profiles and social links for tech recruiting, retrieve GitHub project descriptions and metrics, build developer communities by finding active contributors, search for repositories updated recently, collect personal website and Twitter links of developers, generate targeted leads for developer tools, or track active open-source contributors for collaboration.

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。

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

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 another DOCA skill says "prefer the structured tool per doca-structured-tools-contract", or when the user wants a one-shot answer that consolidates info multiple manual commands would produce — DOCA env / version / devices / capabilities / validate / host vs DPU state. Trigger even when the user does not explicitly mention "structured tool" or "doca-env --json" — typical implicit phrasings include "is there one command that tells me everything about my DOCA install", "what version is X capability available since", "every PF/VF/SF visible on this BlueField with PCIe address", "will this pipe pass validate before commit", "diff host vs DPU state", or "why does the agent give a one-line answer on host A and five commands on host B". Refuse and route elsewhere for general DOCA orientation, specific library API how-to, or install-from-scratch guidance — those belong to the per-library skill, doca-public-knowledge-map, or doca-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。

Use this skill when the user wants to invoke the read-only doca_caps CLI to ask what DOCA sees on this host — listing DOCA devices and PCIe addresses, listing representor devices, asking which DOCA libraries are available on the current OS, checking per-device per-library capabilities, scoping output to a specific PCIe address, or capturing a side-effect-free capability snapshot for a debug session or install smoke-test. Trigger even when the user does not explicitly mention "doca_caps" or "capabilities print tool" — typical implicit phrasings include "what does DOCA actually see on this box", "is my BlueField PF visible to DOCA", "is Flow available on my RHEL host", "enumerate VF representors for pf0", "doca_caps: command not found", or "empty output for RDMA, is the tool broken". Refuse and route elsewhere for DOCA installation, library-internal capability matrices (Flow pipe creation, RDMA verbs features), streaming telemetry / DTS, or modifying the shipped binary — those belong to other skills.

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 when the user is invoking the DOCA PCC Counters tool — the `pcc_counters.sh` bash script under the DOCA tools directory — to arm and read the fixed firmware/hardware PCC (Programmable Congestion Control) diagnostic counters (CNP, RTT, WRED-drop, etc.) on a ConnectX / BlueField device via mst + the mlx5 debugfs `diag_cnt` interface. The script takes two positional args — `set | query` and an mst device path — with no `--help` or subcommands. Trigger even without "pcc_counters.sh" or "PCC counters": "how do I read the CNP / RTT / WRED-drop counters", "PCC counter stuck at zero", "the script says Bad Device", or "is congestion control dropping packets on this port?". Route elsewhere for writing a custom PCC algorithm (doca-pcc), factory firmware PCC config, DOCA install, or fleet-wide CC tuning.

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 to enumerate host↔DPU DOCA comch (formerly Comm Channel) servers and connections via the shipped doca_comm_channel_admin binary — listing comch-capable devices and decoding the per-device server / connection table (server name, PID, in-use / max, PCIe address). The shipped binary is a SINGLE-SHOT SCAN-AND-PRINT tool with no registered arguments — NO list / inspect / drain / restart subcommands; one inventory pass over every comch-capable doca_dev on this side. Channel reset / drain / restart go to doca-comch (program side), doca-setup / doca-hardware-safety (driver reload), or BFB / RShim — NOT to this binary. Trigger on phrasings like "list comch servers", "which channels are active on this BlueField", or "verify admin tool sees same channel as program." Refuse and route elsewhere for the comch programming API, library install, protocol design, channel reset, or general orientation.

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。

Golang ecosystem watch list — official sources (go.dev/blog, pkg.go.dev, tour.golang.org, golang-nuts), newsletters (Golang Weekly, Awesome Go Newsletter), communities (r/golang, gophers.slack.com, Go Forum, go.dev/wiki), blogs (Dave Cheney, Ardan Labs, Rob Pike), YouTube channels (Gopher Academy, GopherCon EU/UK), conferences, and Go contributors to follow on GitHub, X and Bluesky. Use when seeking Golang learning resources, discovering new libraries or tools, finding community channels or meetups, picking Go people to follow, or keeping up with Go language changes and releases. Not for querying a specific module's versions, docs, or vulnerabilities from the CLI (→ See `samber/cc-skills-golang@golang-pkg-go-dev` skill).

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 a live AWS workload with AWS DevOps Agent — incident investigation, root-cause analysis, and release-readiness review — for startups with no dedicated DevOps or SRE engineer. Use when a live AWS workload is misbehaving (production is down, 5xx errors, latency spike, timeouts, it broke after the last deploy, an alarm fired, a pasted CloudWatch alarm or stack trace, find the root cause, write a postmortem, no one on call), for pre-merge review (is this PR safe to ship, blast radius), or to set up, pause, stop, or check the cost of AWS DevOps Agent. Detects existing setup first and never re-onboards. Cost, account access, and code egress are each disclosed in one line with safe defaults: cost and access proceed, code egress stays off unless asked. Do not use for: new architecture (architect-for-startups), scaffolding (start-building-for-startups), migrations (gcp-to-aws, azure-to-aws, heroku-to-aws, llm-to-bedrock), or general Activate and credits questions (knowledge-base-for-startups).

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。

Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device that supports a capability (e.g., CAN, analog input), or checks if required support packages or add-ons are installed. Does NOT connect to, configure, or acquire data from devices — defers to device-specific skills for usage 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。

CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops) or a deploy stuck behind a running deploy task. For stateless HTTP services, prefer HTTP cloud functions.

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[Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase — see postgresql-development skill instead.

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。

Plan the MVP build from a PRD and an MVP concept, as a full development plan or an ultra-lean build spec, with the AI Product Development Toolkit's planning prompts.

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 knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with Azure OpenAI, AI Gateway, MCP tools, Entra auth, or BYO VNet networking, and other Microsoft Foundry related development tasks. Not for Content Safety in Foundry Control Plane (use azure-content-safety), Azure Content Understanding in Foundry Tools (use azure-content-understanding), Azure Speech in Foundry Tools (use azure-speech), Microsoft Foundry Classic (use microsoft-foundry-classic).

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 knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Content Moderator, Content Safety, Content Understanding analyzers, REST/.NET APIs, or document extraction workloads, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).

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 knowledge for Azure Business Process Tracking development including deployment. Use when creating CI/CD pipelines, automating builds, running tests, and deploying tracking solutions via DevOps tools, and other Azure Business Process Tracking related development tasks. Not for Azure Monitor (use azure-monitor), Azure Logic Apps (use azure-logic-apps), Azure Data Factory (use azure-data-factory), Azure Machine Learning (use azure-machine-learning).

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 debugging, bundle analysis, and ecosystem tools for React applications. Use when setting up Vite/webpack build tooling, analyzing bundle size, debugging re-renders with React DevTools, or configuring ESLint and StrictMode for React projects.

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。

R package development with devtools, testthat, and roxygen2. Use when the user is working on an R package, running tests, writing documentation, or building package 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。

Developer Experience specialist for tooling, setup, and workflow optimization. Use when setting up projects, reducing friction, improving development workflows, or automating repetitive tasks. Focuses on making development joyful and productive.

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 LangChain4j patterns for implementing MCP (Model Context Protocol) servers, creating Java AI tools, exposing tool calling capabilities, and integrating MCP clients with AI services. Use when building a Java MCP server, implementing tool calling in Java, connecting LangChain4j to external MCP servers, or securing tool exposure for agent 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。

Structure a dev-tool homepage that converts developers into champions. Use when the landing page is written for the buyer instead of the developer, reads as salesy, buries what the product does, or makes it hard to start. Pairs with the ShipReady homepage audit.

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。

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

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。

Model Context Protocol expert for building MCP servers, tools, resources, and client integrationsUse when "mcp server, model context protocol, claude code extension, building ai tools, tool definition, mcp transport, stdio transport, sse transport, resource provider, prompt template, mcp, model-context-protocol, claude-code, ai-tools, llm-integration, anthropic, server, protocol" mentioned.

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。

Building production-ready Model Context Protocol servers that expose tools, resources, and prompts to AI assistantsUse when "mcp server, model context protocol, mcp tool, mcp resource, claude integration, ai tool integration, mcp, model-context-protocol, anthropic, claude, ai-integration, tools, resources, prompts" mentioned.

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。