「ai platform」の検索結果

Designing conversational flows for website chatbots and AI agents. Intent recognition architecture, branching logic, fallback handling, escalation to human, conversation analytics. Honest about scripted-bot (rigid trees, fail edge cases), hallucinating-bot (LLM without structure, makes things up), and structured-guided-conversation (LLM-powered with intent architecture and fallback discipline) patterns. Distinguishes chatbot DESIGN (this skill) from chatbot IMPLEMENTATION (engineering and platform work). Triggers on chatbot, conversational AI, AI agent, chat widget, intent design, conversational flow, bot escalation, LLM grounding. Also triggers when a chatbot is hallucinating, when a scripted bot is failing edge cases, or when a chatbot is being scoped for the first time.

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。

OpenAI Codex CLI and cross-platform skill authoring. Use when setting up Codex CLI, converting or syncing skills between Claude Code and Codex, configuring agents/openai.yaml, or validating cross-platform skill compatibility.

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 text, images, video, speech, and music via the MiniMax AI platform. Covers text generation (MiniMax-M3 model), image generation (image-01), video generation (Hailuo-2.3), speech synthesis (speech-2.8-hd, 300+ voices), music generation (music-2.6 with lyrics, cover, and instrumental), and web search. Use when the user needs to create AI-generated multimedia content, produce narrated audio from text, compose music, or search the web through MiniMax AI services.

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 paid ad copy for affiliate offers across ad platforms. Triggers on: "write ad copy", "Facebook ad for affiliate", "Google Ads copy", "TikTok ad script", "Pinterest ad", "paid traffic to affiliate", "create ad campaign", "ad headlines", "ad descriptions", "scale with paid ads", "run ads for my affiliate link", "write Facebook ad", "Google Search ad 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。

Use when one master design has to become every size a campaign needs — feed, story, reel, cover, and ad placements: the standard size matrix, three strategies of scale-and-crop, re-compose, or rebuild, safe-zone rules, platform crop behavior, and file naming. Trigger on 'resize this design', 'all the sizes', 'adapt to other placements', 'safe zone', 'standard size chart', 'the text gets cut off in stories'. Also use when one visual exists and six placements are waiting on it. Not for — the original concept brief, see `42-image-brief-global`; production steps in Canva or Figma, see `45-design-tool-brief-global`; the full campaign asset list, see `41-campaign-asset-list-global`; an urgent new creative, see `48-quick-visual-brief-global`.

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 and implement Internal Developer Platforms (IDPs) with self-service capabilities, golden paths, and developer experience optimization. Covers platform strategy, IDP architecture (Backstage, Port), infrastructure orchestration (Crossplane), GitOps (Argo CD), and adoption patterns. Use when building developer platforms, improving DevEx, or establishing platform teams.

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。

Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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。

Owns project and build-level work for Compose and Compose Multiplatform apps: bootstrapping a new project, adopting the kit in an existing project, adding or extracting a module, convention plugins in build-logic, the version catalog, and CI plus agent hooks. Use when starting a Compose Multiplatform app, adding a module, or editing settings.gradle.kts, build.gradle.kts, build-logic, libs.versions.toml, or packaging. Do NOT use for routing and architecture choices (compose-architecture), feature code (compose-feature), repositories and persistence (compose-data), composables or resources (compose-ui), or commonMain vs platform code (compose-platform).

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。

Owns repositories, data sources and mapping for Compose and Compose Multiplatform apps: DTO to domain to UiModel boundaries, Ktor clients and bearer auth, WebSocket and SSE, Room, DataStore, Paging 3, offline-first and data-layer tests. Use when writing or reviewing a repository, data source, DTO, mapper, HttpClient, bearer token, WebSocket, SSE, Room DAO, migration, DataStore, PagingSource, RemoteMediator, offline cache or MockEngine test. Do NOT use for ViewModel or UI wiring (compose-feature), composables (compose-ui), the MVI contract or error tiers (compose-architecture), Gradle modules (compose-project), or commonMain vs platform splits (compose-platform).

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 thumbnail concepts and ideas for YouTube, TikTok, and other video platforms. Creates detailed visual briefs with composition, text, colors, and emotion suggestions. Use when planning thumbnails, improving CTR, or briefing designers.

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 UTM-tagged URLs for campaign tracking. Create consistent, organized tracking links for Google Analytics, HubSpot, and other analytics platforms. Supports bulk generation, naming conventions, and campaign documentation. Use when creating tracking links, campaign URLs, or organizing marketing attribution.

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。

Interview employees to identify recurring daily work, office workflows, and repetitive tasks that can be automated, co-piloted, or supported by AI. Use when the user wants to find what AI can take off their plate, map available tools such as ChatGPT/OpenAI, Claude, Microsoft Copilot, Excel or PowerPoint add-ins, Google Workspace, no-code/RPA tools, coding agents, or internal automation platforms, and write tool-aware specs with fallback paths.

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 MiniMax's first-party Hailuo video API safely and reproducibly across global and mainland-China platforms. Covers current text-to-video, image-to-video, first/last-frame, and subject-reference models; prompt and camera craft; region/account routing; exact cost approval; asynchronous jobs and callbacks; artifact provenance; and rights, likeness, disclosure, and data-governance review. Use when designing, implementing, debugging, or evaluating direct MiniMax/Hailuo video-generation API workflows. Do not use for the consumer Hailuo site, Video Agent templates, gateways, or unrelated MiniMax modalities.

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。

E2B is a cloud platform that gives AI agents secure, isolated sandboxes — ephemeral Linux VMs with a filesystem, package managers, and internet access — to run AI-generated code safely. Use when a user wants an agent to execute Python or JavaScript, install packages, read/write files, or run a long process without risking the host machine, or wants to wire code execution into a LangChain, CrewAI, or custom agent loop.

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。

You are an expert in Cloudflare Workers AI, the serverless AI inference platform running on Cloudflare's global network. You help developers run LLMs, embedding models, image generation, speech-to-text, and translation models at the edge with zero cold starts, pay-per-use pricing, and integration with Workers, Pages, and Vectorize — enabling AI features without managing GPU 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。

Unified multi-platform paid media audit with parallel execution. Spawns scored audits for Google Ads, Meta Ads, and Microsoft Ads simultaneously, merges results into a budget-weighted aggregate health score (A-F), adds cross-platform analysis (budget allocation, tracking consistency, creative alignment, attribution overlap), and produces a prioritized action plan. Optionally generates a client-ready deck via pro-deck-builder. Use when the user asks for a full paid media audit, cross-platform review, or multi-channel ad assessment.

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。

短视频投流 (short-video paid advertising (China platforms)) Master OS — automated mastery of short-video paid advertising (China platforms): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on short-video paid advertising (China platforms) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「投流」「巨量引擎」「千川」「信息流」「创意素材」

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。

数据工程 — 数据平台从业者的认知操作系统, 覆盖把数据从源系统搬运成可靠 / 可查询 / 可信赖形态供分析 / ML / 数据产品消费的全生命周期 (生成 → 摄取 → 存储 → 转换 → 服务 + 安全/数据管理/DataOps/数据架构/编排/软件工程 六条暗流, Reis & Housley 框架): 摄取与集成 (批 + CDC 变更数据捕获 Debezium + EL 工具 Fivetran/Airbyte/Meltano/dlt + Kafka Connect + schema drift) / 存储与文件表格式 (对象存储数据湖 + 列存 Parquet/ORC/Arrow/Avro + 开放表格式 Apache Iceberg/Delta Lake/Apache Hudi + lakehouse + 分区/compaction) / 转换与建模 (ELT dbt/SQLMesh + Spark + 维度建模 Kimball + Inmon + Data Vault + 大宽表 OBT + 渐变维 SCD + 增量模型 + 语义/指标层) / 编排与工作流 (Apache Airflow/Dagster/Prefect/Mage/Kestra/Apache DolphinScheduler + DAG + 幂等 + 回填 backfill + 数据资产调度) / 批流与实时 (Apache Kafka/Apache Flink/Spark Structured Streaming/Kinesis/Pulsar/Redpanda + Lambda vs Kappa + watermark/窗口/exactly-once + 流式 SQL Materialize/RisingWave + 实时 OLAP ClickHouse/Apache Druid/Apache Pinot/StarRocks/Apache Doris) / 数仓与查询引擎 (Snowflake/BigQuery/Redshift/Databricks SQL/Trino/Presto/DuckDB/Polars + 存算分离 + MPP) / 数据质量测试与可观测性 (dbt tests/Great Expectations/Soda + 数据契约 + Monte Carlo data downtime + 新鲜度/量/schema 异常检测) / 数据治理编目与血缘 (DataHub/Amundsen/OpenMetadata/Unity Catalog + 列级血缘 + PII 分类 + 访问控制 + GDPR) / DataOps 与可靠性 (数据 CI/CD + 转换版本控制 + 环境隔离 + 幂等重处理 + 数据 SLA/SLO + 计算存储 FinOps) / 数据架构范式 (现代数据栈 + lakehouse + data mesh + data fabric + 去中心化 vs 中心化所有权) / 分析工程角色 (dbt 时代连接数据工程与分析的桥) — 不含 数据科学/ML 建模本身 (是下游消费者) / BI 仪表盘制作 (serving 下游) / 数据分析报表为终点 / 'data engineer = 跑 Hadoop 的' 过时窄化 / 通用后端应用开发 (平行学科) (Data Engineering — the cognitive operating system of practitioners who design, build, and operate the data platform: moving data from source systems into reliable, queryable, trustworthy form for analytics / ML / products, covering (a) the data engineering lifecycle (generation → ingestion → storage → transformation → serving, with the undercurrents security / data management / DataOps / data architecture / orchestration / software engineering — Reis & Housley framing), (b) ingestion & integration (batch + CDC change-data-capture with Debezium, EL tools Fivetran / Airbyte / Meltano / dlt, Kafka Connect, API + file + database sources, schema drift handling), (c) storage & file/table formats (object storage data lakes, columnar formats Parquet / ORC / Arrow / Avro, open table formats Apache Iceberg / Delta Lake / Apache Hudi, lakehouse architecture, partitioning / compaction / Z-ordering), (d) transformation & modeling (ELT with dbt / SQLMesh, Spark, dimensional modeling Kimball, Inmon CIF, Data Vault, One Big Table / wide tables, normalization vs denormalization, slowly changing dimensions, incremental models, the semantic / metrics layer), (e) orchestration & workflow (Apache Airflow, Dagster, Prefect, Mage, Kestra, Apache DolphinScheduler, DAGs, idempotency, backfills, data-aware / asset-based scheduling), (f) batch vs streaming & real-time (Apache Kafka, Apache Flink, Spark Structured Streaming, Kinesis / Pulsar / Redpanda, the Lambda vs Kappa debate, watermarks / windowing / exactly-once, streaming SQL Materialize / RisingWave, real-time OLAP ClickHouse / Apache Druid / Apache Pinot / StarRocks / Apache Doris), (g) warehouses & query engines (Snowflake, BigQuery, Redshift, Databricks SQL, Trino / Presto, DuckDB, Polars, decoupled storage & compute, MPP), (h) data quality, testing & observability (dbt tests, Great Expectations, Soda, data contracts, Monte Carlo / data downtime, freshness / volume / schema anomaly detection, unit / integration testing of pipelines), (i) data governance, catalog & lineage (DataHub, Amundsen, OpenMetadata, Unity Catalog, column-level lineage, PII / data classification, access control, GDPR / data privacy), (j) DataOps & reliability (CI/CD for data, version control of transformations, environments, idempotent reprocessing, SLAs / SLOs for data, cost / FinOps for compute & storage), (k) data architecture paradigms (modern data stack, data lakehouse, data mesh, data fabric, decentralized vs centralized ownership), (l) the analytics engineering role (the dbt-era bridge between data engineering and analysis); N

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。

GitHub 解封 — 账号封禁/限制/恢复的领域操作系统。覆盖：(a) GitHub 官方政策体系 (TOS / 可接受使用政策 / Trust & Safety 执行模式 / 公开申诉路径 / 受制裁地区解读)；(b) 封号原因诊断学 (spam / abuse / 制裁误标 / 2FA 丢失 / ToS 违规 / 账号劫持误判 / ban evasion 等子类型 + 症状→原因映射 + 自我分诊压测)；(c) 申诉实操 craft (写一封能让 T&S 快速判误伤的英文申诉信 + 升级阶梯 + 法务介入边界 + Don'ts)；(d) 制裁与合规硬边界 (OFAC SDN 名单 / 哪些国家或地区真不可达 / VPN 误判路径 / 中国大陆不是美国制裁地区的反复重申)；(e) 中国大陆开发者特别处境 (sanctioned region 误标 + SMS 验证不支持 +86/+852 + Gitee/GitLab/Codeberg/JihuLab 备用迁移 + 私有自托管 Gitea/Forgejo)；(f) 真实案例库 (~30+ 公开案例分类拆解：误伤 / 真违规 / 制裁误标三类各自赔率与申诉成功路径)。伦理锚绝不软化：不教 ban evasion / 不教撒谎式申诉 / 真违规承认改进 / 丢 2FA 无恢复因子则诚实告知 / 中国制裁误标靠申诉不靠换 VPN / 申诉 6 个月窗口必算清 / 约 3% (业内估) 真违规恢复 vs 约 79% (业内估) 误伤申诉成功率分层标。 (GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: false-positive / genuine violation / sanctions mis-flag, each with win-rate and appeal success path). Ethical anchors absolutely not softened: do NOT teach ban evasion (creating new accounts turns a temp ban into a permanent one — the single biggest mistake); do NOT teach social engineering or lying in appeals (misuse + actually confirms violation); genuine violations: admit + improve beats denial; lost 2FA + no recovery factor → do not pretend recovery is possible; China sanctioned-region mis-flag → fix via appeal, not repeated VPN switching; appeal form 6-month window must be counted carefully; historical 约 3% (业内估) genuine-violation recovery vs 约 79% (业内估) false-positive appeal success rate stratification must be honestly labeled. Anti-samples (explicitly describe harm, never endorse): developer permabanned for ban evasion / open-source team org-banned for personal attacks in public issues / cases where repeated VPN switching escalated risk-control severity.) Master OS — automated mastery of GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: fa

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。

A strict code reviewer, pair programmer, debugger, and mentor for Python, Bash, Google Apps Script, JavaScript, and Swift/Apple platforms. Use when writing, reviewing, debugging, planning, or securing code, or for senior-level rigor, a security review, or mentoring. Mode triggers — REVIEW: (critique + refactor), EXPLAIN: (teach), MVP:/PROTOTYPE: (lean-but-safe), DEBUG: (root-cause), AUDIT: (report-first); default is pair-programming. Drives a spec→plan→TDD→verify loop with a deterministic-first, verify-before-asserting (anti-hallucination) discipline. Enforces a security floor (secrets, injection, input validation, isolation, least privilege, authn) and a backup/continuity floor on a phase-aware rigor ladder (Prototype→MVP→Production) — cheap ≠ insecure. Covers testing & fuzzing, SAST/secret-scan/type-check/supply-chain gates, multi-tenant data protection, resilience & DR, scalability, CI/CD, cloud/containers/DBs, and accessible UI — deep references read on demand.

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。

SE Ranking AI visibility analyst (extension). Tracks AI Share-of-Voice across ChatGPT, Gemini, Perplexity, AI Overviews, and AI Mode in a single query. Highest-impact new extension per the v2 gap analysis — no other vendor covers all 5 AI platforms in one API.

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。

When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' or 'should I run ads.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see cro.

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 social media management for all platforms (LinkedIn, Twitter/X, Instagram, TikTok, Facebook, Pinterest, YouTube). Covers content creation, content pillars, hook formulas, repurposing across platforms, platform-optimized graphics/visuals, content calendar, engagement strategy, analytics/ROI analysis, AI-powered content generation, and scheduling best practices. Use for: social media content, LinkedIn post, Twitter thread, Instagram reels, TikTok, content calendar, social scheduling, engagement strategy, social analytics, social media ROI, content repurposing, social graphics, thumbnails, captions, hashtags, viral content, content creator, social media manager, AI content generation, social media 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。

Front-door router for the product-shots ecosystem. Clarifies underspecified visual creation requests through a 4-stage state machine, injects platform visual DNA (Amazon + 7 social platforms) and industry visual DNA (7 industries), enforces a unified Negative Constraints prompt patch, then routes to one of five downstream business skills (product-shots-main-image / product-shots-detail-page / product-shots-multi-angle / product-shots-ad-creative / product-shots-social-post). Use when the user says "I need a product image", "design something for my listing", "I need content for Instagram", "make an ad for me", "make a cover image", "create a post", "做一个商品图", "帮我做个详情页", "帮我做个广告图", "做一个社媒图", "做一张图", "帮我设计", "做个封面" — i.e. any underspecified visual creation request that needs clarification before generation. This is the intent-routing hub of the product-shots ecosystem.

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。