2,205 件 ・ 関連度順
概要と使いどころ
Use when the user asks to "generate an SEO report", "出月报", "set SEO alerts", or "排名掉了提醒我"; two modes — report builds multi-metric traffic/ranking/authority/content dashboards, and alert configures threshold notifications for future ranking, traffic, technical, backlink, competitor, and AI-visibility changes. Not for raw position-by-position deltas — use rank-tracker. SEO报告/绩效仪表盘/SEO预警/排名监控
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 or update the shared product-marketing context: product, audience, positioning, competitors, jobs-to-be-done, objections, customer language, proof and goals. Use before downstream execution when context is missing.
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 to "measure how our narrative is landing", "track echo rate against our canon lexicon", or "check how AI answer engines describe our brand"; produces a resonance report — echo rate (overlap of market language with the narrative-registry canon lexicon, method declared), AI-answer perception via tavily.py --answer (proxy-labeled), share-of-voice on a locked competitor panel (reusing share-of-voice-tracker), and resonance signals from bluesky.py / gdelt.py / pageviews.py — every number labeled Measured / proxy / User-provided, feeding the TALE E dimension and the upstream of the E1 evidence-integrity veto. Not for rebuilding share-of-voice machinery — use share-of-voice-tracker; not for own-site GA4/GSC analytics — use performance-monitor; not for scoring TALE profile result — use narrative-quality-auditor; not for adjudicating claims — use offer-claims-registry. 回声率/AI回答感知/份额之声/共鸣信号
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 to "pick a launch date", "plan the launch window", or "set the embargo and lift time"; produces a candidate-window comparison table (conflict / tailwind / risk per window) built from industry-event cycles and the competitor launch calendar, a launch-week vs rolling-release format call, store-review buffer padding (labeled Estimated), and an embargo window definition (lift moment + timezone) submitted to the launch registry as a candidate. Not for judging the cultural moment itself — use trend-spotter; not for launch-day execution — use launch-day-conductor. 发布择时/发布窗口/竞品日历/禁运期窗口/审核缓冲
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 to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data. Not for competitor-relative coverage gaps — use content-gap-analysis. 关键词研究/内容选题
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 audit or optimize an App Store or Google Play listing. Also use when the user mentions 'ASO audit,' 'app store optimization,' 'optimize my app listing,' 'improve app visibility,' 'app store ranking,' 'audit my listing,' 'why aren't people downloading my app,' 'improve my app conversion,' 'keyword optimization for app,' or 'compare my app to competitors.' Use when the user shares an App Store or Google Play URL and wants to improve it.
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 to "write SEO content", "draft a blog post / landing page", "update outdated content", or "fix traffic/ranking decay"; two modes — new drafts pages with keywords, headers, snippets, and evidence boundaries; refresh scores decay, prioritizes update work, and produces a republish plan with GEO guidance. Not for AI-citation/GEO readiness scoring — use geo-content-optimizer; not for publish-gate scoring — use content-quality-auditor. SEO文章写作/内容更新/排名恢复
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 to "find content gaps", "竞品写了什么", or "还应该写什么"; builds a competitor-relative coverage map of missing topics, keyword gaps, and editorial-calendar opportunities. Not for raw keyword demand discovery — use keyword-research. 内容缺口/选题规划
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。
Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.
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。
Deep, iterative internet research for current facts, source triangulation, contradiction checks, due diligence, competitive analysis, claim verification, "latest" lookups, and cited reports. Use when the user asks to browse, search, research the web, verify claims, compare sources, gather primary sources, investigate companies, people, products, technical topics, news, events, markets, or create AKBP-ready durable research evidence.
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。
AI-driven Flutter E2E testing via VM Service CLI. Control running Flutter apps in debug mode for smoke tests, regression checks, exploratory testing, and UI automation. Trigger when user mentions E2E testing, UI automation, smoke tests, integration testing, test automation, controlling Flutter apps, VM Service interaction, debugging UI flows, automated regression testing, CI sanity checks, or testing native dialogs/permissions/WebViews. Supports stateful named instances or stateless direct URI connections. Ideal for rapid test feedback, AI agent workflows, element discovery, screenshot capture, log collection, and scriptable UI interactions (tap, scroll, enterText). Use for troubleshooting flaky tests, automating repetitive manual tests, verifying app behavior after merges, or setting up automated QA pipelines.
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-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.
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 you need code research over an indexed codebase with minimal context: structural graph queries (who calls X, call chains, architecture overview, dead code, cross-service HTTP routes) instead of file-by-file grep/read cycles. Also trigger to minimise token spend on repetitive code exploration.
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。
Scrape e-commerce data for pricing intelligence, customer reviews, and seller discovery across Amazon, Walmart, eBay, IKEA, and 50+ marketplaces. Use when user asks to monitor prices, track competi...
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。
Shape FriendlyBet product decisions, MVP scope, user stories, tournament flows, multi-sport expansion, pool mechanics, social competition loops, and feature prioritization. Use when planning what FriendlyBet should build, cut, sequence, or validate, especially for new sports, prediction formats, pool flows, leaderboards, sharing, or product strategy.
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。
Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.
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。
Prompt Injection Challenge: LLMail-Inject The competition features 40 unique levels, each combining
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。
Claw Mar 23, 2026 Comparison 15 min min read OpenClaw vs Other AI Agent Frameworks - Comprehensive C GAP: agent framework / orchestrator SDK: competit
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。
For example: 32-bit float: 4 bytes per parameter 8-bit integer: 1 byte per parameter (75% memory red GAP: public SDK / programmatic API: competitor si
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。
About 5-9 years in, they d notice their teams were no longer getting shit done, and then they d call me.
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。
Mouse Precision Editing Tools for AI Coding Agents HIC Mouse gives AI coding agents precision file editing tools 56% higher accuracy, 58% lower cost,
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。
Protocol ACP | Techzine Oct 08, 2025 Zed Code Editor Adds Agent Protocol for Flexible AI Integration | WebProNews Aug 28, 2025 Google Integrates Gemin
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。
They re context management, tool design, policy gates, memory strategies and, if you want to run loc
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。
PowerContext, Context for work that humans and agents hand off and continue 1 project | news.
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。