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概要と使いどころ
Provision, verify, and connect a self-hosted Temps platform instance on an explicitly authorized machine. Use when the user wants an agent to install Temps with the official deploy script, configure a local CLI context, start browser device authorization, present the approval URL, wait for approval, or perform initial platform, DNS, TLS, user, and service setup without exposing credentials.
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。
TrailSnap 仓库提交、推送、需求平台与 PR 工作流规则。Use when preparing commits, pushing branches, managing the corresponding platform requirement, creating or merging pull requests, or monitoring PR CI in this repository; do not use for ordinary code changes that do not involve submission.
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 real run evidence, validation failures, source drift, platform drift, and user feedback to plan and, only after explicit approval, apply structural upgrades to an existing skill. Use when the user asks to improve an existing skill from recent runs, recurring failures, outdated sources, excessive bloat, changed platform behavior, or validated workflow feedback. Do not use to create a brand-new skill or to execute the business workflow itself.
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 asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to get more from fewer credits, or platform efficiency tips.
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 create a complete multi-shot video, asks how to chain Higgsfield tools together, wants to build a short film or branded content series, asks "what's the full workflow", needs to connect Popcorn → image → video → Recast → audio → assembly, or wants to understand how the platform works as a production system rather than isolated tools.
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 Facebook and Meta ad campaigns, write ad copy, define audiences, and plan budgets. Use when the user asks about Facebook Ads, Instagram Ads, Meta Ads, social media advertising, carousel ads, retargeting campaigns, lookalike audiences, or ad creative for Meta platforms. Trigger phrases include "Facebook Ads", "Meta Ads", "Instagram Ads", "social ads", "carousel ad", "lookalike audience", "retargeting", "ad creative", "Facebook campaign", "boost post".
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 for the owner's personal creator-content thumbnails and covers for short video, Bilibili, Douyin, WeChat, or similar platforms from a title, summary, established real portrait, kangaroo IP, product Logo, screenshot, or app reference. It enforces the owner's visual signature, runs a four-concept selection stage, then five responsive platform ratios. Do not use for generic clients, book or album covers, slide title pages, generic posters or social cards, article body illustrations, document headers, website hero art, or unrelated image edits unless the user explicitly invokes cover-skill and accepts the personal-signature rules.
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。
Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.
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 paid ad AUDIENCES must be researched and defined before launch — target profile, interest and behavior mapping per platform, audience sizing, cold, warm, and hot tiering, lookalike seeds, exclusions, and ranked targeting hypotheses to test. Trigger on 'audience research', 'who should I target', 'interest targeting', 'Meta audience for this product', 'TikTok targeting ideas', 'my targeting is too broad'. Also use when launch is imminent and the ad set targeting is still empty. Not for — persona and JTBD depth for content, see `09-customer-insight-global`; warm retargeting tiers, see `56-retargeting-plan-global`; where the budget goes, see `54-media-plan-global`; the campaign hierarchy, see `52-account-structure-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。
Use when the user needs to choose and stand up marketing channels and the tech behind them — channel selection scoring, platform-by-platform setup checklists, business account and verification steps, and integrations, with region priorities: US Meta plus Google plus LinkedIn, EU adding Xing, SEA adding TikTok, Shopee, Lazada and LINE, LATAM adding WhatsApp Business and Mercado Libre. Trigger on 'channel setup', 'which platforms should we be on', 'set up Google Business Profile', 'marketing tech stack', 'we are starting from zero on social', 'connect our accounts'. Not for — conversion tracking and pixels, see `53-tracking-setup-global`; ad account hierarchy, see `52-account-structure-global`; the posting plan once channels exist, see `01-content-calendar-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。
Use when the user needs PAID ad copy for Meta, Google, or TikTok — six variants across TOFU, MOFU, and BOFU using AIDA, PAS, and BAB, respecting each platform character limit and ad policy, with a dropshipping mode. Trigger on 'ad copy', 'write Facebook ads', 'TikTok ad copy', 'Google RSA headlines', 'primary text for this ad', 'my ad copy is not converting'. Also use when the user has a product page and asks what to run as an ad. Not for — organic social captions, see `37-social-caption-global`; spoken video lines, see `04-script-video-global`; approving copy already written, see `62-marketing-review-global`; the page the ad points at, see `12-landing-page-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。
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
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。
Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
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, or repair .NET tests that use MSTest. Use when a repo uses `MSTest.Sdk`, `MSTest`, `[TestClass]`, `[TestMethod]`, `DataRow`, or Microsoft.Testing.Platform-based MSTest execution. USE FOR: the repo uses MSTest; you need to add, run, debug, or repair MSTest tests; the repo is moving between VSTest and Microsoft.Testing.Platform. DO NOT USE FOR: xUnit projects; TUnit projects. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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 SEO/GEO/AEO analysis toolkit for optimizing content visibility across traditional search engines (Google, Bing), AI platforms (ChatGPT, Perplexity, Claude, Gemini, Grokipedia), answer engines (Google AI Overviews, Bing Copilot, featured snippets), voice assistants (Google Assistant, Siri, Alexa), and social media (Facebook, Twitter, LinkedIn, WhatsApp, Instagram). Analyzes HTML/Markdown/JSX files for metadata completeness, schema markup, keyword optimization, entity extraction, and generates multi-format audit reports with platform-specific recommendations.
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 reviewing, designing, or modifying Java enterprise systems that may support intermediary services, hosting services, online platforms, marketplaces, content moderation, recommender systems, advertising delivery, complaint workflows, transparency reporting, or systemic-risk evidence under the EU Digital Services Act. This should trigger for requests such as Review a Java online platform for DSA controls; Design notice-and-action or appeal workflows; Add recommender, ad transparency, moderation, audit, researcher access, or privacy-safe observability evidence; Assess online-platform transparency controls before production release. Part of Plinth Toolkit
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 reviewing, designing, or modifying Java enterprise systems that expose, exchange, store, process, export, or port data across users, businesses, connected products, cloud providers, APIs, event streams, AI data pipelines, data spaces, or SaaS platforms and need EU Data Act engineering controls. This should trigger for requests such as Review a Java platform for EU Data Act controls; Design data access and portability evidence; Add data-sharing request workflows, export formats, interoperability, metadata, audit logs, cloud-switching support, non-personal data safeguards, or trade-secret handoffs; Assess Data Act engineering readiness before production release. Part of Plinth Toolkit
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。
PyTorch-based ML platform for drug discovery: graph molecular representation learning, property prediction (ADMET, activity), retrosynthesis, drug-target interaction (DTI), and pretraining on large molecular datasets. Provides GNN layers (GraphConv, GAT, MPNN), pretrained models, and benchmark datasets.
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 to research customer pain points, complaints, or sentiment using review platforms like Trustpilot, G2, Capterra, or app stores. Also use when the user mentions "what are users saying", "competitor reviews", "pain points", or "voice of customer research".
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。
Assess company readiness for construction industry uberization. Analyze data transparency, process automation, and competitive positioning against open data platforms.
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。
Convert content between platforms (blog to Twitter thread, article to LinkedIn post, etc.). Optimize for each platform's format, tone, and best practices. Use when user wants to adapt content for different social media platforms.
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。
Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.
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 engaging video scripts for YouTube, TikTok, and other platforms. Creates complete scripts with hooks, main content, and CTAs. Supports various formats including tutorials, vlogs, reviews, explainers, and storytelling. Use when creating video scripts, writing YouTube content, or planning video structure.
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。
Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations, and audience insights for data-driven marketing 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。