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概要と使いどころ
When the user wants to configure canonical URLs, fix duplicate content, or consolidate URL signals. Also use when the user mentions "canonical," "canonical URL," "duplicate content," "duplicate content fix," "preferred URL," or "URL consolidation." For GSC duplicates, use google-search-console.
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 motion design advertisement video prompts for software and tech companies using Seedance 2.0 on Higgsfield. Use whenever the user wants to create a software product ad, SaaS promo, app launch video, tech demo, UI showcase, startup video, or motion graphics for a tech company. Triggers on: software ad, SaaS video, product launch, app promo, tech commercial, UI animation, motion design ad, startup video, product demo video, feature showcase, or any software/tech promotional video request. Use even for "make a video for my app" or "promo for our 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。
Design and run a monitoring system for a website or web app. Use this skill when setting up uptime checks, defining SLOs, configuring error tracking, choosing what to alert on, designing on-call rotations, or fixing alert fatigue. Triggers on monitoring, alerts, uptime, SLO, SLA, error rate, on-call, pager, alert fatigue, observability, dashboards, what should we monitor. Also triggers when an incident reveals a gap in monitoring.
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。
Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality, frequency, and decision relevance). Triggers on user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback. Also triggers when feedback channels overflow with volume that does not produce decisions, when the loudest-voice problem is steering roadmap, or when continuous feedback streams need synthesis discipline.
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。
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。
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
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。
Audits a legal document against legal design principles. Scores the document on six pillars: language patterns (bureaucratese, archaisms, passive voice, nominalization), readability (Flesch Reading Ease and language-specific equivalents), structure and navigation, hidden conditions (material obligations buried away from their headings), statutory duplication (restating the law instead of citing it), and visual hierarchy where layout is available. Assessment-only; does not rewrite the document. Works on English, French, and German documents, inferring the applicable jurisdiction from the document's language and textual signals: governing-law clause, statute citations, party addresses. Use when a user shares a legal document (contract, NDA, T&C, privacy policy, internal policy) asking how good the drafting is from a legal design perspective, whether it is readable, whether it contains buried clauses or restates the law, or how it scores on Flesch / LIX / Amstad / Kandel-Moles readability 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。
AFA design, scope-to-fee matching, negotiation preparation, health check, and scope dispute assessment for in-house legal ops teams managing outside counsel arrangements. Design fee structures (fixed, capped, collar, blended, phased, success). Assess whether scope supports a proposed AFA. Prepare commercial positions for fee negotiations. Review existing AFAs against delivery data. Assess OOS claims and build dispute response. Trigger on: 'structure the fee', 'move off hourly', 'design an AFA', 'does scope support a fixed fee?', 'negotiate the fee', 'renegotiate the arrangement', 'is our AFA holding?', 'fee health check', 'cap is being approached', 'firm is claiming OOS', 'is this in scope?', 'is this OOS?', 'AI should reduce the cost', 'blended rate vs fixed', 'collar arrangement', 'phased fees'.
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。
Collaboration platform configuration methodology for legal matter sites. Site architecture, workflow identification, dashboard design, data quality governance, and user adoption for SharePoint, Teams, and equivalent platforms. M365 is the reference implementation — outputs are platform-agnostic enough to brief IT or build simple automations without becoming a Power Automate manual. Use when setting up a matter site, identifying workflows to automate, designing reporting dashboards, managing platform data quality, or driving user adoption. Trigger on: 'set up the matter site', 'configure SharePoint', 'build a dashboard', 'what should we automate', 'brief IT on this workflow', 'nobody is using the platform', 'data quality is poor', 'set up Teams channel', 'matter site structure', 'alerts and notifications', 'user training', 'platform governance', 'status dashboard', 'what workflows can we automate', 'matter site template'.
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 you want to set up an agent loop, cron-scheduled task, or recurring workflow that runs autonomously. Judgment layer on top of Claude Code's ScheduleWakeup, CronCreate, and /loop — or, on other hosts, cron/GitHub Actions plus a headless agent CLI. Picks dynamic pacing, fixed cron, or a one-shot loop; designs idempotent loop bodies; sets bail-out conditions so loops don't run forever. Examples — weekly review pulse, daily brief, hourly metric monitor, periodic vault compile, upstream-check for an adapted skill. Triggers on "/loopify," "set up a loop," "schedule this task," "run this daily," "run this weekly," "cron this," "make this recurring," "automate this on a schedule," "keep this running until X." Part of the -ify trifecta (skillify / toolify / loopify). NOT for authoring a new skill — that's skillify. NOT for adding a tool/integration — that's toolify.
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 a developmental band system mapping student growth from early childhood through upper secondary. Use when building competency-based curriculum architecture for a school or programme.
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 a learning task where mixed-age students work together with mutual benefit for all age groups. Use when planning cross-age tutoring, vertical grouping, or multi-year group activities.
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 an uninterrupted work cycle with choice-based activities structured within a realistic time block. Use when planning Montessori-style independent work periods or extended choice 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。
Expert GDScript landmine guidance: static typing opcodes, signal-up/call-down, %UniqueName/@onready lifecycle, Callable bind/unbind, await sequences, typed collections, and safe Dictionary iteration. Use for code review, refactoring hot paths, or project standards. Trigger keywords: static_typing, signal_architecture, unique_nodes, @onready, class_name, signal_up_call_down, Callable.bind, typed_collections, await_sequence.
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 Backup development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when protecting Azure VMs, AKS, SQL/SAP HANA, Files/Blobs, or disks with Azure Backup and restore automation, and other Azure Backup related development tasks. Not for Azure Site Recovery (use azure-site-recovery), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network).
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, plan, and analyze A/B tests with statistical rigor. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, sample size calculation, test duration, multivariate testing, or conversion experiments. Trigger phrases include "A/B test", "split test", "experiment", "statistical significance", "sample size", "test duration", "which version wins", "conversion experiment", "hypothesis test", "variant testing".
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 ad account HIERARCHY needs designing or cleaning up — campaign, ad set, and ad structure by objective, a naming convention that keeps data readable, CBO versus ABO by stage, how many ad sets and creatives to run, and the minimum daily budget an ad set needs to exit learning. Trigger on 'account structure', 'campaign structure', 'naming convention', 'how many ad sets should I run', 'CBO or ABO', 'our account is a mess of duplicated campaigns'. Not for — scoring an existing account against 84 checkpoints, see `21-ads-audit-global`; pixel and conversion setup, see `53-tracking-setup-global`; budget across channels, see `54-media-plan-global`; scaling a winner, see `55-scaling-ads-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 disaster recovery strategies with RTO/RPO planning, database backups, Kubernetes DR, cross-region replication, and chaos engineering testing. Use when implementing backup systems, configuring point-in-time recovery, setting up multi-region failover, or validating DR procedures.
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 exactly one finished CRT retro computer-interface illustration from an uploaded portrait, group photo, creature, object, or described theme. Use when the user wants anchored subjects re-authored as an exaggerated circa-1980s bitmap editorial caricature beneath early Macintosh or Minitel-style windows, optionally invoking the exact Chinese presets 街头怪诞, 巨像符号, or 冷面几何. Before generation, collect a named or image-derived palette and aspect ratio through a strict two-stage intake unless supplied. Preserve each intended subject as a distinct identity, one shared pixel lattice, restricted non-skin checkerboard midtones, low-facet geometry, unequal extraction windows, mandatory barrel-curved CRT edges, and the immutable tait-crt-interface-skill title-bar signature. Never trace, auto-pixelate, imitate photographic detail, omit, merge, or duplicate subjects, retry, resize, expose prompts, or ask users to choose a style preset.
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。
ALWAYS USE when asked to fix, rewrite, update, improve, modernize, show corrected code for, or explain existing MSTest tests or MSTest-specific configuration. Use for "review" when corrected code or edits are wanted, even for one pasted assertion or passing tests with bad failure output. Covers expected/actual labels; generic Boolean, collection, string, numeric, null, identity, exception, hard-cast, and object[] checks; TestContext/lifecycle; timeout/cancellation; OS/CI conditions, retry, cleanup, parallelization, MSTest.Sdk project setup, and MSTESTxxxx. Honor the installed MSTest version. DO NOT USE to design new test cases (code-testing), perform report-only audits, create project files rather than explain MSTest setup, run tests, migrate frameworks, or handle non-MSTest/non-.NET code.
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。
Add, configure, or review Ignite UI for Blazor Lite component support in Blazor applications. USE FOR: installing IgniteUI.Blazor.Lite or IgniteUI.Blazor.GridLite, registering AddIgniteUIBlazor() in Blazor Server, WASM, Hybrid, or split Blazor Web App projects, adding @using IgniteUI.Blazor.Controls, wiring the theme stylesheet, picking the right host page, locating the GridLite stylesheet path, explaining single-project vs split Server/Client Web App setup differences, and checking where an interactive render mode is needed for Ignite UI components to work. DO NOT USE FOR: general Blazor component authoring without Ignite UI, choosing app architecture or render mode from scratch (see create-blazor-project), JavaScript interop (see use-js-interop), authentication (see configure-auth), prerendering (see support-prerendering), or layout/component design questions that need no Ignite UI 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 when designing, implementing, reviewing, testing, or cleaning up feature toggles, feature flags, kill switches, runtime configuration gates, canary controls, staged rollouts, experiments, or temporary compatibility switches in Java enterprise systems. This should trigger for requests such as Design a feature toggle strategy; Review this feature flag; Add a kill switch safely; Test toggle on and off paths; Clean up an expired feature toggle; Plan controlled rollout and rollback behavior. 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。
Refactoring pass — extracts repeated Tailwind class combos and markup into components, and lifts magic values into design tokens. Use when the codebase has obvious duplication, hardcoded hex values or pixel sizes, or when the user says "clean this up" / "extract components" / "tokenize styles". Invoke when the user asks for extract on their UI, or mentions 'extract' alongside design / UI / frontend work.
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。
Canonical rules for writing and reviewing reactive code in Shift. Use whenever you add or change code that uses `signal`, `computed`, `effect`, `track`, `peek`, `untracked`, `batch`, `keyedCache`, or `useSignalState`; when you touch the model (`Font`, `Glyph`, `FontStore`, layers), node definitions, render passes, or text layout; and whenever a UI or canvas "doesn't update", updates late, or redraws too often.
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。