「aml」の検索結果

AWT — AI-Powered E2E Testing (Beta) workflow skill. Use this skill when the user needs AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

AWT — AI-Powered E2E Testing (Beta) workflow skill. Use this skill when the user needs AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Avalonia Layout with Zafiro.Avalonia workflow skill. Use this skill when the user needs Guidelines for modern Avalonia UI layout using Zafiro.Avalonia, emphasizing shared styles, generic components, and avoiding XAML redundancy and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Avalonia Layout with Zafiro.Avalonia workflow skill. Use this skill when the user needs Guidelines for modern Avalonia UI layout using Zafiro.Avalonia, emphasizing shared styles, generic components, and avoiding XAML redundancy and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

运行代码生成并检查变更。在修改 API 规范（api-specs/ YAML）或 sandbox OpenAPI/protobuf 后使用。

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 new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.

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 on Claude Code plugins (creating, modifying, testing, releasing, or maintaining) - provides streamlined workflows, patterns, and examples for the complete plugin lifecycle

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 本地配置管理。处理 profile 配置归因、update.mode 的 automatic/disabled 策略、config reset 与历史 yaml 排障；profile 类操作优先使用 `arkcli profile <subcmd>`。

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 resources 实时控制面查询：列出当前/指定 profile 可见资源及其调用兼容性；把 Endpoint 解析为权威模型、模态与候选工作流。read-only，不写 profile.yaml。用户临时给出 ep-... 但未说明该走 Chat、Understand 还是 Gen 时优先使用。反触发：用户已观察到 Endpoint NotFound，并要判断 ID 是否不完整或仅存在于历史用量时，owning skill 必须是 arkcli-infer-endpoint。

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指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 `qwenpaw-data` 命令完成数据任务、选择 `run` 或 `plan`/`execute`、传入 `--datasource-id`、处理长任务输出或排查 CLI 失败的场景。

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 new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.

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。

生成短视频脚本和分镜。输入产品/主题描述、目标受众、时长，输出完整脚本+分镜结构（JSON/YAML）。支持多种模板：痛点-解决、反转剧情、before-after。触发词：视频脚本、短视频文案、分镜、storyboard、video script。

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。

This skill should be used when the user asks to "add an animated background", "build a mesh/gradient background", "make an aurora/shader background", "add constellation/particle background", "animated hero background", or "a subtle looping background behind content". Covers CSS mesh gradients, GLSL shader gradients (Three.js), canvas particle constellations, seamless loops, and reduced-motion/performance handling — fully self-contained.

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 for creating tools using CallableTool2 and Params pattern, plus YAML agent registration

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。

Write, run, and analyze structured test suites for Agentforce agents — functional AND security. TRIGGER when: user writes or modifies test spec YAML (AiEvaluationDefinition); runs sf agent test create, run, run-eval, or results commands; asks about test coverage strategy, metric selection, or custom evaluations; interprets test results or diagnoses test failures; asks about batch testing, regression suites, or CI/CD test integration; requests security testing, OWASP LLM Top 10, red-teaming, penetration testing, prompt-injection tests, a security grade, or a vulnerability assessment of an agent. DO NOT TRIGGER when: user creates, modifies, previews, or debugs .agent files (use agentforce-generate); deploys or publishes agents; writes Agent Script code; uses sf agent preview for development iteration; analyzes production session traces (use agentforce-observe); performs a static safety review of .agent file content (use agentforce-generate Section 15).

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。

Phase B of a WinForms-to-Avalonia migration: extract UI-independent application behavior, state rules, use cases, and boundary contracts with TDD and no WinForms/Avalonia references. Use only when an explicit migration still has business behavior in Forms or UI helpers, or when the orchestrator routes here. Do not build Avalonia XAML in this phase.

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。

Phase D of a WinForms-to-Avalonia migration: build the Avalonia UI shell with composition, MVVM state and commands, responsive XAML, accessibility, localization boundaries, and behavior-focused unit/Headless tests. Use only when an explicit migration is ready to port Forms or when the orchestrator routes here. Prefer this over control-by-control ports.

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。

Phase C of a WinForms-to-Avalonia migration: implement platform and infrastructure adapters for dependencies discovered in Phase A/B, such as persistence, process execution, dialogs, notifications, or environment capabilities. Use only in an explicit migration when such dependencies leak into Forms/core or when the orchestrator routes here. Do not invent adapters for capabilities the product does not have, and do not implement main-window XAML.

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。

Design well-structured agent loops with best-practice coaching and cross-model review gates before you run them. Use when the user wants to design, build, or set up an agent loop, iterative agent workflow, self-review loop, LLM-as-judge loop, multi-model council, reviewer/judge gate, or goal-driven looping process. Guides goal refinement, typed verification criteria, reviewer/judge selection, privacy boundaries, termination guards, and observability, then emits a RUN_IN_SESSION.md handoff prompt plus portable loop.yaml, loop.resolved.json, LOOP.md, and run-loop.py.

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, validate, and enrich Open Knowledge Format (OKF) bundles — the open spec for representing organizational knowledge as markdown files with YAML frontmatter. Use when the user mentions 'OKF', 'Open Knowledge Format', 'knowledge bundle', 'OKF bundle', 'create a knowledge base for agents', 'validate OKF', 'convert to OKF', 'enrich knowledge docs', 'agent-readable knowledge', 'LLM wiki', 'knowledge catalog', 'kcmd', or wants to structure knowledge as markdown files for AI agent consumption. Also use when the user has a directory of markdown files and wants to make them interoperable or conformant with the OKF standard. Even for simple requests like 'make this folder OKF conformant' — the skill has critical structural rules the agent needs.

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。

ESPHome device configuration, firmware, and IoT product development. Covers ESP32, ESP32-S3, ESP32-C3, ESP32-C6, ESP32-H2, ESP32-P4, ESP8266, RP2040, RP2350, nRF52, LibreTiny, Shelly, Sonoff, Tuya, BLE proxy, Matter firmware, Thread, Zigbee, GPIO, sensor YAML, LVGL displays, LED strips, voice assistant hardware, device flashing, Arduino conversion, alarm_control_panel, lock, valve, media_player, microphone, speaker, audio DAC, event entities, datetime entities, Z-Wave proxy, MIPI DSI displays, and DLMS smart meters. Also covers designing new ESPHome-based products: hardware selection, component sourcing, PCB design (KiCad), enclosures, 3D printing, CE/FCC certification, BOM optimization, and manufacturing from prototype to production scale.

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。

Reference guide for connecting popular APIs to Home Assistant via Node-RED, YAML, or custom integrations. Covers authentication, endpoints, and complete working examples for: energy APIs (Tibber, Nordpool), weather (SMHI, OpenWeatherMap, yr.no), transport (SL, Trafikverket, Resrobot), smart home clouds (Shelly, Tuya, Philips Hue, IKEA), and global APIs (OpenAI, Spotify, Google Calendar, Telegram, GitHub). Use this skill whenever the user mentions a specific external service, API, or data source they want to connect to Home Assistant - even if they don't say "API".

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Use when an agent must stand up the OpenClaw↔Cognee integration with FalkorDB as the vector + graph store. This skill is SELF-CONTAINED — it tells you to generate every file (Dockerfile, sitecustomize.py, docker-compose.yaml) from the exact contents below, build a custom Cognee image that loads the FalkorDB adapter, run Cognee + FalkorDB together, self-verify the adapter registered, and point the OpenClaw cognee plugin at it (including per-agent graphs). No other files in this directory are required.

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, edit, validate, and import Monitors-as-Code YAML files. CLI-first; falls back to MC MCP tools, then manual 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。