「query」の検索結果

Use when building Spring Boot applications with Neo4j using Spring Data Neo4j (SDN 7.x/8.x) — @Node entity mapping, @Relationship, @RelationshipProperties, Neo4jRepository, ReactiveNeo4jRepository, @Query annotations, application.yml configuration, projections, Neo4jClient, Neo4jTemplate, transactions, auditing, or Spring AI Neo4jVectorStore vector search. Does NOT handle raw Java driver code without Spring — use neo4j-driver-java-skill. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver version upgrades — use neo4j-migration-skill.

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Orchestrates zero-to-running-app in 8 stages — prerequisites → context → provision → model → load → explore → query → build. Each stage reads its own reference file. Supports HITL and fully autonomous operation. Use when starting a new Neo4j project from scratch, provisioning Aura, generating synthetic data, building a notebook or app, or running the full onboarding pipeline. Time budget ≤15 min autonomous, ≤90 min HITL. Does NOT cover Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or Cypher migration — use neo4j-migration-skill. Does NOT cover CLI/admin tasks on an existing DB — use neo4j-cli-tools-skill.

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Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.

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Use when writing or changing a query against PostgreSQL from Go — avoiding N+1 loops, reading EXPLAIN output, indexing, and keyset pagination

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Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

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Designs or reviews relational, document, key-value, graph, or search data models with ownership, invariants, access paths, migrations, consistency, retention, privacy, and recovery behavior. Use for schema changes, new data stores, indexes, migrations, persistence boundaries, or query-driven design. Not for a query-only bug without a model change or for API contract design.

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Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.

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Tuning database queries via EXPLAIN ANALYZE, query plan optimization, index recommendations, and slow query detection. Not for schema/migrations (Schema) or non-DB performance (Bolt).

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Filter Temu products by multiple dimensions (keyword/product ID/store ID, front/backend categories, price, rating, reviews, total/weekly/daily sales, listing date, fully-managed/semi-managed, semi-managed regions, tags, etc.). Triggered when users mention Temu products, Temu product selection, Pinduoduo cross-border, Temu bestsellers, Temu semi-managed, fully-managed products, Temu product query, or temu items. Even if the user does not mention the tool name, this skill should be triggered whenever searching for products, viewing sales/ratings/prices, or filtering products on Temu.

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Filter Temu stores by multiple dimensions (store name/ID, country site, backend category, fully-managed/semi-managed, total/weekly/monthly sales and revenue, rating, reviews, followers, product count, store opening time, etc.). Trigger when users mention Temu store, Temu store analysis, Temu seller, Temu store ranking, Temu semi-managed store, Temu revenue, temu stores, Temu store query. Even if the user does not mention the tool name, trigger this skill whenever they are looking for stores on Temu, filtering store data, or analyzing store performance.

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Filter Shopify standalone store products by multiple dimensions (keyword/URL, price, weekly sales, listing date, Facebook ads, competitiveness, supplier availability, shipping country, etc.). Triggered when users mention Shopify products, Shopify product selection, standalone store product selection, Shopify bestsellers, Shopify dropshipping, standalone store sourcing, Facebook ad products, Shopify product query, or shopify items. Even if the user does not mention the tool name, this skill should be triggered whenever searching for products, viewing weekly sales/revenue/competitiveness, or filtering products on Shopify standalone stores.

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Web search, online retrieval, real-time information query, search engine search, Reddit and other community platform discussions, external site posts and trending topics. Trigger when users need to search for the latest information online, look up recent news or trends, query real-time data, research topics via search engines, browse Reddit or community discussions, discover external site posts and trending topics, obtain any online content, web search, online lookup, real-time information, news search, Reddit, trending topics, search engine. Even if the user does not explicitly say "search", trigger this skill whenever their intent involves obtaining real-time web information or verifying current facts.

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Query TikTok Shop store (seller) details, retrieving a complete store profile by sellerId with total sales, multi-period (1d/7d/30d/90d) sales and GMV, followers, rating, review count, positive feedback rate, delivery rate, response rate, in-store product count, promoting creator count, promotional video count, livestream count, price range, product categories, and estimated listing time. Trigger when users mention TikTok store detail, TikTok seller detail, TikTok store analysis, TikTok store data, TikTok store profile, TikTok Shop store detail, TikTok seller detail, Nexscope store profile. Even if the user does not explicitly mention "Nexscope" or "TikTok", trigger this skill whenever their need involves querying the full detail/profile of a specific TikTok Shop store (with a known sellerId).

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Batch query TikTok product detail data, including multi-period sales and GMV (1d/7d/15d/30d/60d/90d/cumulative), live sales and live GMV, promoting video and creator data, views, price, rating, review count, commission rate, and delisted/fully-managed status. Supports batch retrieval by product ID or TikTok Shop product URL. Trigger when users mention TikTok product detail, batch query TikTok products, TikTok product sales analysis, TikTok product GMV, TikTok live sales, TikTok influencer sales data, TikTok product price rating, batch get TikTok product info, Nexscope product detail, TikTok product detail, batch product lookup, TikTok sales analysis, TikTok GMV, TikTok live sales, TikTok influencer data. Even if the user does not explicitly mention "Nexscope", trigger this skill whenever their need involves batch retrieval of detailed TikTok product sales and marketing data by product ID or product URL.

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Query TikTok e-commerce product leaderboards via Kalodata and query detailed data for specific products. Supports viewing high-ranking/hot-selling products by region, currency, language, and date range, and using productId to retrieve price range, sales, revenue, commission rate, listing/delisting time, and owning shop. Trigger when users mention TikTok product ranking, TikTok bestseller chart, TikTok top products, kalodata product rank, TikTok product detail, TikTok product profile, product price, product sales, TikTok product ranking, TikTok bestseller chart, TikTok top products, kalodata product rank, TikTok product detail, kalodata product detail, product analytics. Even if the user does not explicitly mention "kalodata", trigger this skill whenever their need involves viewing TikTok product leaderboards or detailed data for a specific TikTok product.

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。

Filter Shopify standalone stores by multiple dimensions (store name/domain, country, years since creation, product count, ad count, monthly visits, monthly orders, social media followers, etc.). Triggered when users mention Shopify stores, Shopify store analysis, standalone stores, Shopify sellers, competitor standalone stores, Shopify monthly visits, standalone store ad library, shopify stores, or Shopify store query. Even if the user does not mention the tool name, this skill should be triggered whenever searching for stores, filtering store data, or analyzing store performance on Shopify standalone stores.

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。

Query patent family information from Nexscope (Nexscope) by patent ID or publication number. Triggered when users mention patent family, patent family search, simple family, INPADOC family, Nexscope family, family patent lookup, patent equivalents, family members, cross-border related patent lookup, patent family, family patents, patent equivalents, cross-border patents, Nexscope, or INPADOC family. Even if the user does not explicitly say "patent family," this skill should be triggered whenever their need involves querying family members, equivalent patents, or related cross-border applications for one or more patents.

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。

Query patent bibliographic (catalog) information from the Nexscope patent database by patent ID or publication number. Triggered when users mention patent bibliographic info queries, patent catalog information, patent applicant queries, patent inventor queries, patent classification codes, patent abstract retrieval, patent citation analysis, patent priority claims, patent application citations, patent examiner information, patent bibliographic data, inventor lookup, applicant lookup, patent classification, patent metadata, Nexscope, or patent citations. Even if the user does not explicitly mention "bibliographic info," this skill should be triggered whenever their need involves querying detailed metadata for a specific patent by patent ID or publication number.

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。

Query patent simple bibliographic (catalog) data from the Nexscope patent database. Triggered when users mention patent bibliographic information queries, patent basic info retrieval, patent catalog data, patent publication details, searching by patent number for inventors, patent applicant information, patent abstract retrieval, patent classification codes (IPC/CPC), patent citation queries, or any request to search for structured metadata by patent ID or publication number, patent brief bibliography, patent basic info, patent number lookup, patent abstract, Nexscope, or patent metadata. Even if the user does not explicitly mention "Nexscope" or "bibliographic info," this skill should be triggered whenever their need involves querying core bibliographic fields of specific patents.

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Query patent legal status information from the Nexscope (Nexscope) database. Triggered when users mention patent legal status, patent validity check, patent status query, patent event history, simple legal status, legal events such as transfer, license, pledge, opposition, litigation, re-examination, patent legal status, patent validity, patent events, transfer/license/pledge, Nexscope, or patent status lookup. Also triggered when users ask whether a patent is active, inactive, pending, expired, granted, withdrawn, or revoked, or want to look up legal status by patent ID or publication number.

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Nexscope Ozon product detail query: fetches the complete detail of a single Ozon product by SKU, returning title, price (RUB), rating, review count, QA count, total and daily average sales within the stats window, revenue, stock, category ranking, daily sales trend, brand, seller, fulfillment method (FBO/FBS/OZON), weight, and listing time/days/months. Use for single product deep analysis, competitor product teardown, Ozon product selection assessment, listing diagnosis, sales trend and category ranking tracking. Trigger when the user mentions Ozon product detail, Ozon single product analysis, Ozon SKU query, competitor product data, Ozon sales trend, Ozon category ranking, Ozon stock, Ozon listing time, Nexscope Ozon product search, Ozon product detail, Ozon SKU lookup, single product analysis, competitor product teardown, Ozon sales trend, category rank. Also trigger when the intent is to view detailed data of an Ozon product, even without explicitly mentioning Nexscope.

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Query and analyze Nexscope data for Amazon niche market insights, including market metrics, buyer reviews, competitive landscape, price trends, and growth trends. Trigger when the user mentions niche market analysis, market insights, niche market data, market competition analysis, brand concentration, new product launch success rate, out-of-stock rate, price trends, review insights, market demand score, niche market insights, market metrics, competition analysis, price trends, growth trends, Nexscope data, market intelligence, out-of-stock rate. Even if the user does not explicitly mention "Nexscope" or "niche market", if their need involves querying market-level intelligence for a specific Amazon niche market by market ID, this skill should also be triggered.

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 Nexscope data to reverse-lookup traffic keywords for any Amazon ASIN, including organic ranking, ad ranking, search volume, traffic share, organic/paid scores, ABA TOP3 click concentration, click conversion rate, year-over-year search volume changes, and weekly/monthly time windows. Trigger when the user mentions ASIN keyword analysis, ASIN reverse lookup, traffic keyword research, organic ranking query, ad ranking query, keyword position tracking, Nexscope keyword data, competitor keyword peeking, viewing which keywords drive traffic to a product, analyzing keyword performance for a specific ASIN, time windows by week/month/recent N days, ASIN reverse keyword lookup, traffic keywords, organic ranking, ad ranking, search volume, Nexscope keywords, competitor keyword reverse lookup, click concentration, click-to-purchase conversion, week-over-week search volume. Even if the user does not explicitly mention "Nexscope", if their need involves finding keywords associated with a specific Amazon product (ASIN), this skill should also be triggered.

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。

Query Codex banked reset credits from the local Codex Desktop login state and report available reset count plus expiration times. Use when the user asks to check Codex reset credits, reset opportunities, reset chances, reset count, rate-limit reset credits, or expiration times; also use when the user provides a codex-reset-credits-skill or codex-reset-credits runbook link and asks Codex to query the result directly.

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。