654 件 ・ 関連度順
概要と使いどころ
Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.
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 Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.
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。
Preview Convex spend — rank functions by bytes/documents-read × call-volume from insights, project each cost driver's growth curve, name the cheapest fix; confirm-cost for paid actions.
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 every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.
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。
Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.
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。
Analyze product data and manage product tooling in PostHog. Use when the user wants product analytics or insights, HogQL/SQL queries, feature flags, experiments and A/B tests, error tracking, session replay, surveys, LLM analytics, dashboards, data warehouse, or PostHog documentation.
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。
Quickly capture product ideas, feature requests, or insights from meetings and conversations. Rapid documentation with smart categorization and deduplication.
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 effective data visualizations using best practices for clarity, accuracy, and visual communication of 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。
Access real-time crypto token data, DeFi analytics, wallet intelligence, project research, and blockchain insights through Heurist Mesh agents. Use when the user asks about token trends, DeFi protocols, wallet holdings, project due diligence, Twitter/X crypto sentiment, or deeper market analysis.
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。
This skill helps users extract YouTube video transcripts and perform deep competitive analysis on the content. Agent should proactively apply this skill when users express needs like analyze YouTube video content strategy, perform competitive video content analysis, extract and analyze YouTube subtitles for marketing insights, understand competitor value propositions from their videos, identify target audience from YouTube video content, analyze pain points and needs mentioned in YouTube videos, evaluate competitor CTA strategies in video content, find content gaps in competitor YouTube videos, analyze video narrative structure and hooks, extract key messaging and positioning from YouTube content, benchmark competitor video content quality, research competitor marketing angles through video analysis, identify audience signals and terminology level in videos, analyze emotional tone and persuasion techniques in YouTube content.
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。
This skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.
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。
Translate natural language to SQL, optimize query performance, and interpret EXPLAIN plans for SQLite and PostgreSQL. Triggered when users ask to convert questions into SQL, improve slow queries, tune indexes, analyze execution plans, or mention keywords like NL2SQL, query tuning, or full table scan.
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。
Inspects Observal traces, sessions, rankings, feedback, telemetry health, logs, and Agent insight reports. Use when the user wants operational evidence, current activity, telemetry diagnosis, ratings, report generation, regression analysis, or recommendations grounded in Agent usage.
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。
Save ideas, observations, content topics, projects, and convictions in <ideas-repo>. Use when the user asks to capture an idea or insight. Adds to idea backlogs, not reminders or tasks.
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。
Check the health of published EAS Updates: crash rates, install/launch counts, unique users, payload size, and the split between embedded and OTA users per channel. Use when the user asks how an update is performing, whether a rollout is healthy, how many users are on the embedded build vs OTA, or wants to gate CI on update health.
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。
Full SEO audit combining Google Search Console, URL Inspection API, PageSpeed Insights, a technical crawl, keyword research, and metadata, schema, search intent and Core Web Vitals checks. Surfaces quick wins, diagnoses traffic drops and content gaps, and produces an actionable 30-day plan. Use whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, search visibility, technical SEO, URL indexing, or LCP, INP, CLS or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger.
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工作经验知识库管理。适用于用户明确要求'保存到Obsidian'、'记录这个'、'save this insight'、'memo this'、'capture this'等知识沉淀场景。将对话中的提示词、模式、问题修复、想法和效率优化保存到Obsidian知识库，并自动同步到GitHub。
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。
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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。
Automate Instagram tasks via Rube MCP (Composio): create posts, carousels, manage media, get insights, and publishing limits. Always search tools first for current schemas.
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 mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.
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。
查询用户自己在 Easel 已登录的小红书、抖音、快手、知乎和视频号身份、粉丝、获赞、关注及作品列表。 当用户问“我登录了哪些号、我是谁、我的粉丝/获赞、我最近发了什么、我有哪些帖子”时，先用本 SKILL 查本地登录态，不要先向用户索要账号名或链接。 某条帖子的评论抓取与分析分别用 skill-xhs-comment-reply 和 skill-comment-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。
评论区量化分析：对一批评论做情感分析（正/中/负占比 + 代表评论）、高频词与短语提取、 以及需求/吐槽/提问的诉求挖掘，为内容复盘和选题反哺提供数据。当用户说"评论情感分析" "评论区分析""用户在说什么""评论正负面比例""评论高频词""评论关键词""口碑分析""评论词云" "用户诉求""评论区吐槽"时使用。基于 jieba（分词）+ SnowNLP（情感）+ 社媒情感词典。
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。
Report wiki ingestion/completeness state, pending source delta, structural insights, or maintenance equilibrium. Use for remaining-work/status questions, hubs and bridges, or whether maintenance skills still have pending changes. wiki-digest summarizes learned knowledge instead.
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。
Explaining how the business is doing, meaning why a metric moved, which segment drove it, pace against a comparable, progress against goals the operator has stated, and questions over sales, traffic, conversion, and customers or this operation's equivalents that the snapshot alone does not answer. Not needed when the snapshot's headline figures and their change on the prior period answer the question, how a period went included.
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。