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概要と使いどころ
Add a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.
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 LoopX must manage a multi-PR or multi-MR delivery program across one or more repositories: inventory current change requests, reconcile new/merged/closed or retargeted work, preserve requirement and dependency priorities, maintain a roadmap document, or monitor material lifecycle/check/review changes over time. Use provider-neutral snapshots and one grouped continuous monitor; do not use for deep per-PR code review, approval, commenting, or merge 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。
Review code changes for concrete defects.
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。
Generate release notes in 3 formats (CHANGELOG.md, PR body, Slack announcement) from git commits. Automatically categorizes changes and converts technical language to user-friendly messaging. Use for releases, changelogs, version notes, what's new summaries, or ship announcements.
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。
Generate a conventional commit message for staged changes
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 changes, detect scope issues, and create a well-structured PR
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 structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
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。
Fetch customer reviews for a Taobao or Tmall product by itemId, returning reviewer name, date, purchased variant, review text, and photo URLs. Use when user asks to get product reviews from Taobao, scrape Taobao customer feedback, extract buyer reviews by item ID, collect Tmall ratings and comments, 采集淘宝商品评价, 抓取淘宝买家评论, 获取淘宝商品评论, 天猫商品评价抓取, 按商品ID获取评价. Also applies to sentiment analysis of product reviews, building review datasets, and monitoring product rating changes.
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。
Walmart product detail page extractor: given a walmart.com product URL (walmart.com/ip/...), extract full product data including itemId, title, brand, model, UPC, price, wasPrice, currency, availability, category path, seller info, all images, shortDescription, longDescription, product highlights, full specifications as key-value map, color/size variants with item IDs, fulfillment options (shipping/pickup/delivery with dates), return policy, and review summary with rating breakdown. Use when user mentions walmart product detail, walmart item page, walmart product page, scrape walmart product, extract walmart item, walmart product data, walmart item details, walmart product info, walmart product scraper, walmart item scraper, walmart product URL, walmart ip URL, walmart.com/ip, walmart specifications, walmart product specs, walmart product images, walmart variants, walmart color options, walmart size options, walmart seller info, walmart return policy, walmart fulfillment options, walmart shipping info, walmart availability, walmart product enrichment. Also applies to enriching a list of walmart product URLs with full details, monitoring walmart product price and availability changes, building a walmart product catalog, competitive product research on walmart, and batch collection of full product data from walmart item IDs.
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。
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
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 structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.
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。
Automatically check code changes since last tag and update documentation in docs/ directory (en, zh-CN, ja-JP) and CLAUDE.md to ensure consistency with actual code implementation
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 changes with Git only and auto-generate conventional commit messages with optional emoji; suggests splitting commits when needed, runs local Git hooks by default (use --no-verify to skip)
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 pull request based on current branch changes
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 version release and code commit using changeset
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 git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.
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 a reviewable GitHub pull request from the current branch with a Conventional Commits title, a concise evidence-based body, and before/after screenshots for UI changes. Use when asked to open, create, publish, or prepare a PR.
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 implementing, debugging, or reviewing Nexent frontend pages, React components, hooks, API services, TypeScript types, styling, or localization under frontend/. Includes UI requests without file paths. Skip backend-only work, Python tests, and documentation-only changes with no frontend behavior.
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 and maintain Nexent's traditional Python UT for product changes and bugfixes under test/backend, test/sdk, and test/ext_components. Cover unit behavior, boundaries, errors and regression assertions with isolated pytest tests. Formal D1-D5 assets in test-e2e use nexent-test-assets.
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。
Sync delta specs from a change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change.
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。
Holistic, system-aware planning before implementing non-trivial tasks. Use when the task involves new features, architectural decisions, multi-file changes, unclear requirements, or multiple valid approaches. Triggers on "/plan", "plan this", "design an approach", "let's plan first".
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 should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review.
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 should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.
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 for TeamHarness shared workspace paths, filesync, artifact publication, and Matrix room file boundaries, including artifact publish_file and task/project deliverables. Do not use for message routing or project state changes.
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。