seo
無料Optimize for search engine visibility and ranking. Use when the task involves `improve SEO`, `optimize for search`, `fix meta tags`, `add structured data`, `sitemap optimization`, or `search engine optimization`.
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。
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概要と使いどころ
Optimize for search engine visibility and ranking. Use when the task involves `improve SEO`, `optimize for search`, `fix meta tags`, `add structured data`, `sitemap optimization`, or `search engine optimization`.
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。
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.
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。
Work with the Toss Securities Open API for Korean and US stock market data, stock info, exchange rates, market calendars, account and holdings lookups, order history, buying power, sellable quantity, commissions, conditional orders, rankings, trading trends, market indicators, realtime WebSocket integration, and delegated trading workflows. Use when an agent needs to run user-delegated buy/sell/order-management loops, call or build against developers.tossinvest.com, inspect the Toss OpenAPI schema, generate client code, or operate with TOSS_API_KEY/TOSS_SECRET_KEY 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。
Entry point for reading PANews cryptocurrency / blockchain news, market narratives, and Polymarket smart money leaderboards. Triggers: today's headlines, breaking news, trending rankings, article search, reading specific articles, browsing columns / series / community topics, industry events & conferences, event calendar, platform hot searches and editorial picks, latest smart money boards, board highlights, and board comparisons.
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。
Evaluates fund performance against peer universes with vintage year comparison, quartile ranking, and strategy-specific benchmarking. Use when benchmarking fund performance, analyzing vintage comparisons, or assessing relative positioning.
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-assisted debugging specialist with deep knowledge of modern debugging tools, observability platforms, and automated root cause analysis. Implements Cursor Debug Mode methodology — structured hypothesis ranking, targeted code instrumentation, human-in-the-loop reproduction gate, log-confirmed root cause, and mandatory cleanup.
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 7-phase SEO optimization workflow covering technical SEO auditing, keyword research strategy, on-page optimization, content SEO and E-E-A-T, structured data implementation, link building, and AI search optimization. Use when auditing search engine visibility, diagnosing ranking issues, implementing schema markup, conducting keyword research, optimizing content for E-E-A-T signals, or adapting for AI-driven search (AI Overviews, SGE).
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。
Orchestrate multi-LLM parallel debate and synthesis. Dispatches prompts to available omega CLI wrappers in parallel, collects independent responses, runs anonymized peer review ranking, and synthesizes via a chairman model. Supports collaboration templates, idle watchdog, inter-agent messaging, worktree isolation, and multi-turn sessions. No server required.
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。
Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical (restaurant, healthcare, legal, home services, real estate, automotive). Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "local rankings", "service area", "multi-location", or "local search".
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 evidence-labeled semantic cores for SEO, LLM-readable architecture, and site information design. Use this skill when the user asks for semantic core, query clusters, search intents, audience segments, entity/topic maps, language or locale priorities, competitor/source evidence, pillar-topic planning, or a structured handoff before URL architecture and internal linking. It must mark unknown search volume, difficulty, and ranking data as unknown instead of inventing 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。
Purify water from wild sources using boiling, filtration, and chemical methods. Covers source assessment and priority ranking, sediment pre-filtering, method selection (boiling, chemical, UV, filter), altitude-adjusted boiling procedure, chemical treatment dosages, and safe storage practices. Use when needing drinking water in a wilderness setting, when available water sources are of unknown quality, in an emergency survival situation where dehydration is a risk, or when making water safe for cooking or wound cleaning.
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。
Compute relative and absolute binding free energies with the Open Free Energy toolkit — the rigorous alchemical alternative to docking scores when a congeneric series needs reliable potency ranking. Use this skill to plan a perturbation network over a ligand set, choose atom mappings, run hybrid-topology or separated-topology protocols, and analyse the result — per-edge ΔΔG with uncertainty, cycle-closure error, and mean unsigned error against measured affinities. Also trigger on OpenFE, alchemical transformation, thermodynamic cycle, RBFE, ABFE, SepTop, lambda window, MBAR, cycle closure, or perturbation map.
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。
Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.
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, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
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。
Sector Rotation & Analysis — analyzes sector momentum rankings across all 11 GICS sectors, money flows, economic cycle positioning, relative strength, top stocks per sector, valuations, and rotation signals. Triggered by "trade sector <sector>" or "trade sector rotation".
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。
Uses OpenSEO as the measured SEO data plane for keyword volume and difficulty, SERPs, ranked keywords, backlinks, local SEO, rank tracking, Search Console, GA4, and site audits. Use for measured SEO metrics, indexing evidence, organic analytics, local rankings, backlink profiles, or rank trackers. Prefer OpenSEO over guessed metrics when connected; otherwise continue with qualitative web research and mark numeric metrics unknown.
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-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor backlinks", "beat <competitor>", "competitor seo teardown".
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。
Work with the @upstash/redis TypeScript/JavaScript SDK, a serverless HTTP-based Redis client for Next.js, Vercel, Cloudflare Workers, edge runtimes, and Node.js. Use when adding a cache (cache-aside, write-through, TTL and expiration strategies), session storage and user sessions, a key-value store, leaderboards and rankings with sorted sets, counters, distributed locks, queues with lists, streams and consumer groups, sparse index-addressed arrays and ring buffers (ARSET, ARINSERT, ARRING, ARGREP, AROP), embeddings and nearest-neighbour vector search stored inside Redis (VECTOR commands via redis.vector, separate from @upstash/vector), JSON documents, pipelines and MULTI/EXEC transactions, Lua scripting, read replicas, or full-text search, typo-tolerant search, facets, aggregations, and search over Redis stream entries with Upstash Redis Search (different from regular FT.SEARCH; also available for TCP clients via @upstash/search-redis and @upstash/search-ioredis). Also use when migrating from ioredis or node-redis, when a Redis connection is needed from a serverless function without connection pooling, when integrating @upstash/ratelimit, or when the user says Redis cache, KV store, session store, serverless Redis, or Upstash Redis. Also use when building AI agents on Redis with Upstash AgentKit (agent memory, chat history, RAG tools, tool caching, chat persistence, resumable streams, distributed locks) for the Vercel AI SDK, TanStack AI, or Vercel Eve. Supports automatic serialization/deserialization of JavaScript types.
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。
Chinese journal matcher — performs L3 6-dimensional matching (keywords, cited direction, trend, solicitation, institution, cross-discipline), calculates conditional acceptance probability with review cycle estimation, and outputs tiered submission strategy (aspiration-stable-safety) using 4-layer weighted ranking.
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。
International journal matcher — performs L3 6-dimensional matching for SCI/SSCI/EI/Scopus journals, computes conditional acceptance probability with review cycle estimation, applies 4-layer weighted ranking, and outputs tiered submission strategy including CAS warning screening and Chinese scholar friendliness 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。
Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.
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。
Diagnose and audit SEO issues affecting crawlability, indexation, rankings, and organic performance.
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。
"Measure social media influence using engagement-weighted metrics beyond follower count. Use this skill when the user needs to evaluate influencer effectiveness, compare influence across accounts, or build an influence scoring system — even if they say 'who is more influential', 'influencer ranking', or 'measure social impact'.".
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。
"Implement PageRank algorithm to compute web page importance scores using the random surfer model. Use this skill when the user needs to rank pages by link authority, build a simplified search ranking system, or understand how link structure determines page importance — even if they say 'which pages are most important', 'link analysis', or 'page authority score'.".
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。