「automated」の検索結果

iOS 应用上架大师 (审核 + ASO + 合规 + 国内/海外多区 + 付费策略) (iOS App Store launch — submission, review, ASO, compliance, post-launch monetization) Master OS — automated mastery of iOS App Store launch — submission, review, ASO, compliance, post-launch monetization: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on iOS App Store launch — submission, review, ASO, compliance, post-launch monetization problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「iOS 上架」「App Store 上架」「App 审核」「App Review」「TestFlight」

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。

Interactive escalation-resolution workflow for the bmad-loop orchestrator. A bmad-loop run paused on a CRITICAL escalation (a contradiction or gap a dev/review session could not safely resolve alone); you and the human disambiguate the frozen spec so the story can be re-driven. Invoked as /bmad-loop-resolve <story-key>. Unlike the automated dev/review sessions this session is interactive — a human is present and you SHOULD ask.

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 an AI agent (or any external script) needs to play-test a running Pixi'VN game end-to-end in a real browser — starting the game, advancing/branching the story, answering input prompts, going back, and reading/writing storage — via `Game.testing`, the opt-in devtools bridge exposed on `window`. Load this before wiring up automated/agent-driven playtesting, not for authoring story content itself (see `pixi-vn-narration`).

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。

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

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。

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development 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。

Semantic topic cluster planning and automated execution engine for claude-blog. Performs SERP-based keyword research, groups keywords by search intent and SERP overlap, builds a hub-and-spoke cluster architecture, generates an interactive SVG cluster map, and executes the full cluster by orchestrating blog-write calls with shared cluster context and automatic internal-link injection. Fills the strategy-to-execution gap: blog-strategy plans the blueprint, blog-cluster builds the house. Use when user says "blog cluster", "topic cluster", "content cluster", "cluster plan", "cluster execute", "pillar content", "hub and spoke", "content ecosystem", "cluster map".

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。

Builds end-to-end predictive modeling pipelines on tabular datasets—data exploration, preprocessing, baseline modeling, and mandatory optimization—producing valid saved predictions in the required output format. Use for any supervised machine learning or data modeling task, including classification and regression on tabular data, Kaggle-style competitions or submission-file challenges, training a model to predict a target from features, or requests to fit/tune/evaluate models with scikit-learn, XGBoost, Random Forest, Logistic Regression, and similar non-deep-learning methods. Runs fully automated end-to-end without asking the user for intermediate decisions.

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 set up automated daily promotion / marketing for their Claude Code skills — researching how top skills are promoted on marketplaces (ClawHub / openclaw / SkillsMP / agentskills.io), generating a per-skill marketing plan, auto-posting to X (Twitter) via xurl, and drafting community discussion posts (Reddit / HN / Discord). Triggers — "推广 skills", "营销 skills", "自动发推广", "每天自动推广", "skill marketing", "promote my skills", "/wjs-promoting-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 when a newly mined VoiceDrop article needs automated post-processing — invoked headless by the 5-minute poller (launchd com.jianshuo.voicedrop-postprocess) with the article stem as argument. Triggers — "/wjs-voicedrop-post-processing <stem>".

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。

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development 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。

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

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。

Automated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness verification.

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 building or changing any interactive mobile UI - VoiceOver/TalkBack labels, grouping, headings, focus order, Dynamic Type/font scale, reduce motion, contrast, and the automated check for each stack.

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。

Run the critical path smoke test gate before QA hand-off. Executes the automated test suite, verifies core functionality, and produces a PASS/FAIL report. Run after a sprint's stories are implemented and before manual QA begins. A failed smoke check means the build is not ready for QA.

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 a QA test plan for a sprint or feature. Reads GDDs and story files, classifies stories by test type (Logic/Integration/Visual/UI), and produces a structured test plan covering automated tests required, manual test cases, smoke test scope, and playtest sign-off requirements. Run before sprint begins or when starting a major feature.

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。

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

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。

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development 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。

Producing automated feature demo videos via Playwright E2E tests: scenario design, recording config, implementation patterns, quality checklists. Use for product demos or onboarding material.

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。

Remediating known failure patterns automatically from Triage diagnoses and Beacon alerts: runbooks with safety-tier classification, staged verification, rollback. Use for automated remediation.

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。

Reviews PRs that add or modify Agent Skills, checking structural validity, design quality, and marketplace consistency. Use when reviewing skill file changes, auditing SKILL.md quality, or running automated skill PR reviews.

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。

Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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。

Run Univer Sheets, Docs, Slides, Bases, Boards, or PDFs in Node.js without browser UI. Use for server-side or backend Univer, OSS Sheets or Docs Node presets, Pro product Facades and collaboration, JSON snapshot processing, formula or Base child-process workers, or automated unit manipulation with @univerjs/rpc-node.

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 a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for "automated reports", "scheduled report", "email digest", or "Slack alerts for metrics".

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 automated regression suites — golden sets, threshold alerting, CI integration for model changes. Use when asked to "catch model regressions in CI", "build a golden set", or "automate eval regression".

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。