「metadata」の検索結果

Upload one Kleros-ecosystem file per paid request to IPFS through the Kleros x402 gateway for $0.01 USDC on Base mainnet. Use for dispute evidence, MetaEvidence JSON, court/dispute/arbitrator policies, Curate item metadata, juror justifications, or any artifact a Kleros contract or subgraph will reference by CID. Trigger when the request mentions Kleros, court, arbitrator, dispute, juror, Curate, Proof of Humanity, evidence, meta-evidence, justification, explicitly names this gateway or skill, or asks to test or validate it. Do NOT use for generic IPFS/CID requests without Kleros context; recommend a general-purpose pinning service. Each request accepts exactly one file: different bytes require separate paid uploads, while identical bytes should reuse one CID.

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Use when a user mentions Jupiter token verification, VRFD eligibility, paying 1000 JUP to verify a token, submitting a verification request, or updating metadata via the Jupiter express verification flow.

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Metaplex development on Solana — NFTs, tokens, compressed NFTs, candy machines, token launches, autonomous agents. Use when working with Token Metadata, Core, Bubblegum, Candy Machine, Genesis, Agent Registry, or the mplx CLI.

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Manage the user's shared agent-skill library via skills-manager-cli — install, update, remove, deploy or undeploy skills per agent, manage presets, organize tags, search, and adopt existing skills. Use this whenever the user wants Claude Code, Codex, Cursor, or another agent to gain or lose a skill, wants to organize the central library, or asks what is installed or deployed. Prefer this over direct agent-folder installs because Skills Manager preserves source metadata, preset membership, updates, and cross-agent deployment state.

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Review Apache Pinot concurrency and state safety when locks, shared callbacks, lifecycle, or distributed metadata change.

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Audit version freshness, FR/EN parity, and metadata quality of all whitepapers and recap cards

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Audit a project or library of skills for metadata, trigger boundaries, workflow completion criteria, local resource closure, instruction economy, tool scope, effort, and routing evidence. Use before shipping skills, after importing a skill collection, or when a skill triggers too often or not at all.

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Deep-crawl any website from start URLs, return per-page LLM-ready text/markdown/HTML plus metadata (title, description, author, language, canonical URL, OG) and in-scope outbound links. Use when user mentions deep crawl website, recursive crawl, crawl a whole site, scrape entire website, scrape docs site, scrape documentation, scrape knowledge base, scrape blog, build RAG corpus, build vector database from website, knowledge base for chatbot, GPT knowledge files, llms.txt, sitemap crawl, BFS crawl, scrape with depth or page limit, include exclude URL globs, remove boilerplate, strip navigation header footer, website to markdown, website to text, multi-page extraction, bulk page scraping, clean markdown from URL, docs site to markdown corpus, site to clean corpus. Also applies to building RAG pipelines, indexing a customer site, syncing docs into a vector store, generating training corpora from any docs hub, or expanding a single start URL into a clean corpus of every reachable in-scope page.

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TikTok keyword search video scraper: input search keyword → output paginated video list with full metadata (author, engagement stats, music, video meta). Use when user mentions TikTok search scraping, search TikTok by keyword, TikTok search results, extract TikTok search data, scrape TikTok videos by keyword, TikTok keyword videos, TikTok keyword search, TikTok search results collection, find TikTok videos by topic, tiktok search scraper, tiktok keyword scraper. Also applies to market research on TikTok content for specific topics, competitor content monitoring, or discovering videos and creators around a keyword.

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TikTok hashtag video scraper: input a hashtag name → output paginated video list with full metadata (author profile, engagement stats, music, video meta, hashtag list). Use when user mentions TikTok hashtag scraping, TikTok tag videos, scrape TikTok by hashtag, extract TikTok hashtag data, TikTok challenge videos, get videos from a TikTok tag, bulk collect TikTok hashtag posts, TikTok video collection by tag, TikTok topic videos, collect TikTok tag data, batch fetch TikTok videos by hashtag, tiktok tag scraper, tiktok challenge scraper. Also applies to competitive research on TikTok trending topics, influencer discovery by hashtag, content monitoring for specific TikTok tags, or any task requiring video lists from a specific TikTok hashtag or challenge.

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TikTok user profile video scraper: input a TikTok username → output the user's profile info plus paginated video list with full metadata (engagement stats, music, video meta). Use when user mentions TikTok profile scraping, scrape TikTok user videos, get TikTok creator videos, extract TikTok profile data, TikTok user posts, TikTok account video collection, collect TikTok profile page videos, TikTok creator video list, TikTok creator data, TikTok profile scraper, tiktok user scraper, tiktok creator scraper. Also applies to influencer research, competitor analysis, content archiving for a specific TikTok creator, or extracting all posts from a TikTok account.

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Fetch Xiaohongshu (RedNote / xhs) note detail and comments by note ID, returning title, description, author info, engagement stats, tags, and paginated comment list. Use when user mentions note detail xiaohongshu, get rednote post, xhs note content, xiaohongshu comment scrape, fetch post comments, scrape xhs comments, rednote note details, xiaohongshu post engagement, xiaohongshu note content, rednote post data, xhs post detail, get xiaohongshu comments, rednote comment list, xiaohongshu note metadata, xhs note scrape, fetch rednote note.

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This skill helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.

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Scrapes posts from a Facebook group given a group URL, sort order, and desired count — returns structured post metadata including post_id, permalink, author, timestamp, body text, images/videos, reaction counts, reaction type breakdown, comment count, and share count. Use when: user wants to scrape/extract Facebook group posts, collect FB group content, harvest group data, get posts from a Facebook group, monitor Facebook group activity, bulk export group posts, facebook groups scraping, facebook-groups-scrape-posts, fetch FB group feed.

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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。

Etsy product detail scraper: given an Etsy listing URL, returns full product detail including listingId, title, priceCurrent, priceOriginal, currency, images (all), description, shopName, shopUrl, rating, reviewCount, favorites, inCartCount, variations (with per-option price ranges), highlights, listedDate, relatedTags. Use when user mentions Etsy product, Etsy listing detail, Etsy item info, Etsy product page, scrape Etsy listing, extract Etsy product data, Etsy price and variations, Etsy product images, Etsy product description, Etsy shop from listing, Etsy favorites count, Etsy sale count, Etsy variations extraction, Etsy listing metadata, single Etsy product scrape, bulk enrich Etsy listing URLs, Etsy product details export. Also applies to competitor product monitoring, price and variation tracking on a specific listing, favorites/wishlist popularity tracking, description mining for SEO analysis, and any per-listing enrichment task.

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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.

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This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

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Own MSBuild generated-artifact integration. USE FOR: a target that creates or should create source, Content, None, or another physical file but the artifact is missing from compilation or output; target timing; evaluation-time glob misses; $(IntermediateOutputPath) placement; and FileWrites clean tracking. The prompt may describe the generated artifact without naming the producing task. DO NOT USE when the primary defect is general Include/Remove/Update semantics, item metadata or batching, duplicate/overlapping declarations, or a generated-item identity relationship; use item-management. Exclude Roslyn source-generator internals and non-MSBuild systems.

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Guides creation and modification of ASP.NET Core Web API endpoints with correct HTTP semantics, OpenAPI metadata, and error handling. USE FOR: adding new API endpoints (controllers or minimal APIs), wiring up OpenAPI/Swagger, creating .http test files, setting up global error handling middleware. DO NOT USE FOR: general C# coding style, EF Core data access or query optimization (use optimizing-ef-core-queries), frontend/Blazor work, gRPC services, or SignalR hubs.

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Read and write a Zotero library from the shell with the `zotero-cli` command - search papers by keyword or meaning, read PDF full text and page ranges, get and set metadata, manage collections, tags, notes and annotations, add items by DOI/URL/ISBN, and export bibliographies. Use whenever the user asks about their Zotero library, references, citations, papers they have saved, or their reading notes.

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Meme coin and token security audit — rug pull detection (honeypot, hidden mint, fee manipulation, LP lock bypass), Solana SPL token analysis (freeze authority, mint authority, metadata mutability), Token-2022 extension risks (transfer hooks, permanent delegate), DEX liquidity pool attacks (sandwich amplification, LP drain, bonding curve exploits), pump.fun/Raydium/Jupiter integration risks, token_scanner.py automation, and real exploit examples from 2024-2025. Use for any token audit, rug pull assessment, meme coin security review, or pre-investment due diligence.

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Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告

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。

VMware vSphere / vCenter Server external attack matrix — version fingerprinting, the high-impact CVE chain (CVE-2021-21972 vRealize unauth file upload, CVE-2021-21985 vSAN plugin RCE, CVE-2022-22954 Workspace ONE SSTI, CVE-2023-20887 Aria RCE, CVE-2024-37085 ESXi AD bypass, CVE-2023-34048 vCenter DCERPC OOB write APT-exploited), default credentials, SSO configuration disclosure, vmdir LDAP enumeration, ESXi Open SLP RCE history. ONLY for vCenter / Workspace ONE / Aria instances exposed to the internet — internal-network vCenter is out of scope per the external-only boundary. Use when recon shows port 443 with vCenter banner, `/ui` redirect, `/websso/SAML2/Metadata`, or VMware product fingerprints.

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。