「format」の検索結果

Detect and search for similar utility/invention patents based on product information. Trigger when users mention utility patent detection, patent infringement risk, patent similarity search, patent screening, invention patent search, patent risk assessment, TRO (Temporary Restraining Order) risk analysis, utility patent, invention patent detection, patent infringement risk, patent search, TRO risk, Ruiguan. Even if the user does not explicitly say "utility patent", trigger this skill whenever their need involves checking whether a product may infringe existing utility/invention patents before selling in a target market.

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 Walmart product details via Nexscope, including pricing history and sales trends. Trigger when users mention Walmart product detail, Walmart product data, Nexscope, Walmart price trends, Walmart sales trends, Walmart product detail, Walmart price history, Walmart sales trend, Nexscope product. Even if the user does not explicitly mention "Nexscope", trigger this skill whenever their need involves viewing detailed information, historical price changes, or sales trends for a single Walmart 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。

Search TikTok e-commerce store leaderboards via Kalodata and query detailed information for specific stores. Supports viewing high-ranking, high-sales TikTok Shop stores by region, currency, language, and date range, and using shopId to retrieve revenue, sales volume, on-sale product count, self-operated/affiliate/shopping mall channel revenue, and creator collaboration count. Trigger when users mention TikTok store ranking, TikTok shop leaderboard, TikTok top shops, TikTok store ranking, TikTok Shop store ranking, kalodata store search, kalodata store ranking, TikTok store detail, TikTok shop profile, store revenue, store sales, TikTok shop ranking, TikTok shop leaderboard, TikTok top shops, TikTok store ranking, TikTok shop detail, TikTok store detail, kalodata shop search/detail. Even if the user does not explicitly mention "kalodata", trigger this skill whenever their need involves viewing TikTok store leaderboards or detailed data for a specific TikTok store.

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。

Search TikTok e-commerce creator leaderboards via Kalodata and query detailed profiles for specific creators. Supports viewing top-performing influencer-sellers by region, currency, language, and date range, and using creatorId to retrieve follower count, video/live revenue and GPM, contact information, and associated shops. Trigger when users mention TikTok creator search, TikTok creator ranking, TikTok influencer leaderboard, TikTok creator detail, TikTok creator profile, creator homepage data, creator contact info, TikTok creator search, TikTok creator ranking, TikTok influencer leaderboard, TikTok creator detail, creator analytics, kalodata creator search/detail. Even if the user does not explicitly mention "kalodata", trigger this skill whenever their need involves viewing TikTok creator leaderboards or detailed sales performance data for a specific TikTok creator.

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。

Nexscope Ozon Russia product search and reverse lookup. Searches Ozon products in the Nexscope database by Russian keyword or SKU, returning product ID, title, brand, and seller information. The entry point for Ozon product discovery and competitor analysis chains. Trigger when the user mentions Ozon product selection, Ozon product search, Russian e-commerce product selection, Ozon keyword search, Ozon SKU query, Nexscope Ozon, Ozon product search, Nexscope Ozon, Russian marketplace, Ozon SKU lookup, Ozon keyword search. Also trigger when the intent is to discover or reverse-lookup products on Ozon Russia by keyword or SKU, even without explicitly mentioning Nexscope.

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 Overview (AI Mode) scraping via Google Search. Returns AI-summarized key points for a single keyword, ideal for deep research, technical Q&A, long-tail product selection, and cross-border consumer preference analysis using the latest web information. Single-round only; follow-ups require the agent to summarize context and issue a new request. Triggered by: Google AI, AI Overview, AI Mode, Google AI search, AI search, deep research, consumer preference analysis, web summary, long-tail product research, cross-border market 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。

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.

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 forward citation details from the Nexscope patent database. Triggered when users ask about patent citations, cited patents, cited references, patent references, forward citations, prior art citations, or want to see which patents and non-patent literature specific patents cited during the application process, patent cited references, forward citations, patent references, citation analysis, or Nexscope. When users provide a patent ID or publication number and need citation information, even if they do not explicitly say "forward citation," any request about which references a patent cited applies.

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。

Retrieves patent claims data from Nexscope (Nexscope). Trigger when the user mentions patent claims, claim text, independent claims, dependent claims, claim count, claims tree, claims analysis, claim scope, claim language, viewing the claims section of a specific patent, patent claims, independent claims, dependent claims, claims text, Nexscope. Also trigger when the user requests patent claims information by patent ID or publication number, even without explicitly mentioning Nexscope or Nexscope.

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。

Retrieve detailed Amazon product information by ASIN, including title, Item Highlights when extractable from raw HTML, images, bullet points, specifications, A+ content, pricing, ratings & reviews, variants, and more. Trigger when users mention Amazon product details, ASIN lookup, Item Highlights, product page data, listing analysis, bullet point extraction, product image retrieval, variant inspection, competitor listing research, price lookup, review breakdown, product specification query, or similar terms. Even if the user does not explicitly say "product details," trigger this skill whenever the request involves retrieving structured data from Amazon product pages via ASIN.

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。

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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。

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.

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 evidence-first engineering discipline to any agent-built software project: fact discovery before action, evidence-calibrated status reporting, explicit change boundaries and stage gates, controlled confirmation for risky or external actions, sensitive-information redaction for anything shared publicly, and resumable continuity after interruptions. Use when users ask an agent to take over an existing codebase, deliver a feature across stages, verify whether work is actually complete, judge release readiness, or keep conclusions honest about what is proven versus assumed. This foundation skill is domain-neutral; vertical suites (for example mini-program engineering) build on it by adding domain facts and platform rules.

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 evidence-first engineering for WeChat and other mini programs from a vague idea or existing repository through project discovery, product specification, architecture, implementation, debugging, device adaptation, verification, and release readiness. Use when users ask to build a mini program from zero to one, take over an existing mini-program project, deliver a cross-stage feature, diagnose project status, coordinate development and testing, or judge whether a mini program is ready to upload or release. Enforces fact discovery, change boundaries, stage gates, evidence-calibrated status, sensitive-information redaction, and continuity after side questions.

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。

Verify mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local success into device, cloud, release, or formal acceptance 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。

Use this when managing Python dependencies with uv, running tests with pytest, linting with ruff, formatting code, type checking with mypy, or executing notebooks.

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。

Design a source evaluation protocol using lateral reading and credibility checks for digital information. Use when students need to evaluate websites, online sources, or social media 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。

Define the scope and purpose of a complex inquiry before mapping or futures work begins. Use when a class or group needs to agree what they are investigating, who it matters to, and at what scale.

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。

Design an error analysis protocol to diagnose the root cause of student mistakes and misconceptions. Use when error patterns appear in student work and targeted feedback is needed.

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。

Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.

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。

Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.

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。

Design a diagnostic hinge question that reveals whether students understand enough to move on. Use when planning key checkpoints mid-lesson during explicit or direct instruction.

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。

Interpret learning analytics data and translate dashboard findings into actionable teaching decisions. Use when reviewing LMS data, quiz patterns, or engagement 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。