本文へ移動
cccskills

「querying」の検索結果

269 件 ・ 関連度順

概要と使いどころ

td

無料

Manage tasks and issues with the td CLI. Use for creating, tracking, querying, and handing off work items. Covers task lifecycle, session management, structured handoffs, epics, dependencies, and boards.

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。

espennilsen/pi1222026年10月12日 更新

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.

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。

firecrawl/skills1222026年10月9日 更新

Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.

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。

neo4j-contrib/neo4j-skills1152026年10月12日 更新

codebase

無料

Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Codex.

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。

topoteretes/cognee-integrations992026年10月13日 更新

codebase

無料

Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Antigravity.

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。

topoteretes/cognee-integrations992026年10月13日 更新

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.

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。

firecrawl/opencode-firecrawl992026年10月6日 更新

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

ruvnet/agentdb912026年10月12日 更新

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).

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

Retrieves translated patent claims from the Nexscope (Nexscope) patent database. Trigger when the user asks about patent claims, claims translation, viewing claims in specific languages (Chinese, English, or Japanese), querying patent claims by patent ID or publication number, analyzing claim text, claim translation, patent claim translation, Nexscope, patent translation. Also trigger when the user needs patent claim content in a specific language, even without explicitly mentioning translated claims.

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

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.

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

Query Amazon product detail and historical trends by ASIN using Nexscope data, covering 14 marketplaces. Trigger when the user mentions Nexscope product detail, ASIN detail query, sales trends, price curves, price history, BSR ranking history, BSR trends, profit analysis, FBA fee analysis, gross margin, product trend analysis, daily/monthly sales, revenue trends, Deal promotion history, product detail, sales trend, price history, BSR ranking, profit analysis, FBA fees. Even if the user does not explicitly mention "Nexscope", if their need involves querying Amazon product detail or historical trend data by 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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

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。

nexscope-ai/nexscope-ecommerce-skills892026年10月9日 更新

Bioactivity and small-molecule data-side catalog. Covers ChEMBL search/lookup, MolTrack compound and batch registration, HitTriage / HitDesign / PeptiHit workflows, and Curves dose-response analysis (IC50/EC50 fitting). Open this skill when the user asks about querying ChEMBL, registering or looking up compounds in MolTrack, running a hit-triage campaign, or fitting/inspecting dose-response curves.

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。

datagrok-ai/public742026年10月14日 更新

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

plurigrid/asi672026年7月10日 更新

Dasel v3 selector patterns for Maven POM XML files — use when querying dependency versions, filtering by groupId or scope, extracting module hierarchy from parent POMs, or detecting version conflicts across enterprise multi-module Java projects. Load this skill when working with pom.xml files using dasel.

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Manages feature implementation task state via SAM MCP tools. Use when querying task status, listing ready tasks, dispatching tasks for execution, updating task timestamps, or coordinating multi-task feature rollout. Activated by the /dh:execution orchestrator to track progress — also activates directly when managing 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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Dasel v3 selectors for Spring bean factory XML — use when querying any Spring ApplicationContext XML for bean discovery, dependency wiring, JMS destination mapping, property injection extraction, or cross-bean reference tracing. Load this skill before writing dasel selectors against Spring bean XML files (applicationContext.xml, *_beans.xml, spring-*.xml).

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Dasel v3 patterns for querying Tomcat web.xml deployment descriptors — use when inspecting servlet enumeration, filter chain discovery, listener listing, context parameter extraction, or init-param inspection in web.xml files

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Dasel v3 query patterns for InstallAnywhere .iap_xml installer definitions — use when querying action sequences, discovering variables, resolving platform conditions, navigating panels, or comparing installer variants. Files are 2.5+ MB, 65,000+ lines — too large for context reads, requires structural dasel 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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

Use when querying, modifying, or converting JSON, YAML, TOML, XML, CSV, HCL, or INI with dasel v3. Complete reference for selectors, functions, conditionals, variables, spread operator, type casting, and format-specific patterns.

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。

Jamie-BitFlight/claude_skills672026年10月13日 更新

IOTA blockchain MCP server providing wallet management with human-in-the-loop signing, Move smart contract build/test/publish, and on-chain queries via JSON-RPC and GraphQL. Use when interacting with IOTA network from AI coding agents, managing IOTA wallets, building or publishing Move packages, querying on-chain objects or transactions, or checking epoch and network statistics.

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。

Scottcjn/iota-agent-mcp662026年8月20日 更新