「discover」の検索結果

Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup

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 shell tools safely in sandboxed environments by discovering files from real workspace roots instead of assumed user folders, then explicitly verifying output artifacts after generation.

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。

Plan customer discovery interviews with the right goal, segment, constraints, and method. Use when preparing interviews for problem validation, churn research, or new product ideas.

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。

Run a full discovery cycle from problem hypothesis to validated solution. Use when a team needs a structured path through framing, interviews, synthesis, and experiments.

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。

Builds Agent-to-Agent (A2A) servers and clients following Google's open protocol for agent interoperability. Use when the user wants to create an A2A-compliant agent, build an Agent Card, implement task management, connect agents across frameworks, set up agent discovery, handle streaming responses, implement push notifications, or orchestrate multi-agent workflows. Trigger words: a2a, agent to agent, agent2agent, a2a protocol, a2a server, a2a client, agent card, agent interoperability, agent collaboration, multi-agent, agent discovery, a2a sdk, a2a task.

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。

OKX-aggregated DeFi (no specific DApp named) — product discovery, deposit/withdraw/claim execution, AND positions viewing. **If the user names ANY third-party protocol/DApp (Aave, Lido, PancakeSwap, Uniswap, Curve, Compound, Morpho, Pendle, Kamino, Raydium, Hyperliquid, Polymarket, …), route to okx-dapp-discovery — NOT here, even for 'show my Aave positions'.** INVEST triggers: 'invest in DeFi', 'earn yield', 'find best APY', 'deposit/stake for yield', 'search DeFi products', 'redeem/withdraw position', 'claim DeFi rewards', 'borrow against asset', 'repay loan', 'add/remove CLMM liquidity', 'APY/TVL history', 'depth chart', yield farming, lending, staking, liquidity pools. PORTFOLIO triggers: 'check my DeFi positions', 'view DeFi holdings/portfolio', 'my staking/lending positions', 'DeFi balance', 'DeFi 持仓', '我的DeFi资产'. Do NOT use for: DEX swaps (okx-agentic-wallet), token prices (okx-dex-market), wallet token balances (okx-agentic-wallet).

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。

HARD BLOCK — never use for prediction-market/Polymarket UpDown queries; route to okx-dapp-discovery when a named DApp (Polymarket/Aave/Hyperliquid/PancakeSwap/Morpho) appears with a timeframe, or 涨跌/updown for BTC/ETH/SOL/XRP/BNB/DOGE/HYPE. Otherwise, read-only on-chain DEX data, 6 groups: TOKEN (search, hot/热门, liquidity, holders/whale, risk metadata, cluster/持仓集中度, trade history, top traders); MARKET (price/价格, K线/OHLC, index price, wallet PnL/胜率, trade history); SIGNAL (smart money/KOL/whale tracking, buy signals/信号, leaderboard/牛人榜); SOCIAL (news/新闻, sentiment/情绪, token vibe/热度, KOL leaderboard); TRENCHES (pump.fun/meme launches/新盘/扫链, dev reputation, bundle/sniper detection/捆绑狙击者, co-investor — read-only; buy/snipe → okx-dapp-discovery); WS (onchainos ws CLI, or custom WebSocket script/脚本). Also owns Market API payment/x402, quota/额度, and MARKET_API_*_OVER_QUOTA/confirming:true for all 6 groups.

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。

LI.FI REST API for cross-chain and same-chain token swaps, bridging, DeFi deposits (Composer), yield discovery (Earn), and intent-based execution (Intents). USE THIS SKILL WHEN USER WANTS TO: - Swap tokens between different blockchains (e.g., "swap USDC on Ethereum to ETH on Arbitrum") - Bridge tokens to another chain (e.g., "move my ETH from mainnet to Optimism") - Swap tokens on the same chain with best rates (e.g., "swap ETH to USDC on Polygon") - Find the best route or quote for a token swap across chains - Deposit into DeFi vaults/lending/staking in one click, including cross-chain (Composer: Aave, Morpho, Pendle, EtherFi, Yearn, etc.) - Discover yield opportunities, vault APY/TVL data, or track DeFi positions (Earn) - Execute gasless or intent-based transfers via a solver network (LI.FI Intents) - Move stablecoins cheaply with optimized defaults (stablecoin preset) - Build multi-chain payment flows (accept any token, settle in specific token) - Check supported chains, tokens, bridges, or gas prices - Track status of a cross-chain transaction, recover from failed/partial transfers - Query transfer history/analytics or withdraw collected integrator fees - Build backends, bots, or AI agents (any language) that need cross-chain functionality

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。

Analyzes the current project to surface high-value Routines use cases across the three trigger types (schedule, API, GitHub events). Usage: /routines-discover

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。

Discovers Threads user accounts by keyword, extracting profile data including username, display name, verification status, biography, and follower count. Use when user asks to find Threads accounts, search Threads profiles, discover Threads users by keyword, look up Threads creators, find influencers on Threads, search for people on Threads, get Threads user details, collect Threads profile information, find accounts related to a topic on Threads, search Threads for accounts by name or keyword, or enumerate Threads users matching a search term.

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 discover key contacts across industries, roles, and social platforms via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding public profiles for founders or CEOs, discovering key decision-makers in a specific industry, extracting contact details for lead generation, searching for growth leaders on LinkedIn or Facebook, gathering professional networking profiles, retrieving URLs and names of industry leaders, finding marketing managers in a specific field, conducting competitive analysis by identifying key personnel, sourcing talent acquisition targets across platforms, or compiling a list of target roles on specific social sites.

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。

MUST USE when an existing .NET test project was excluded from a .slnf/CI solution filter, disappeared from .sln/.slnx discovery, or lost its production ProjectReference; also for requests to set up, create, reuse, add, register, include, or repair a test project. Handles "tests pass directly but CI discovers zero", exact solution wiring, xUnit/NUnit/MSTest, and central packages. DO NOT USE to only author tests in an already-wired project (code-testing), run tests, migrate, or correct MSTest syntax/configuration without changing project or CI files (writing-mstest-tests).

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。

Compares two or more dotnet new templates side by side to help users choose between them based on parameters, feature support, frameworks, and classifications. USE FOR: deciding between similar templates (webapi vs webapp, blazor vs blazorwasm, console vs worker), producing a side-by-side comparison of parameters and feature support, understanding how templates differ before creating a project. DO NOT USE FOR: creating a project from a template (use template-instantiation), authoring or validating custom templates (use template-authoring and template-validation), general single-template discovery (use template-discovery).

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。

Web2 recon pipeline — subdomain enumeration (subfinder, Chaos API, assetfinder), live host discovery (dnsx, httpx), URL crawling (katana, waybackurls, gau), directory fuzzing (ffuf), JS analysis (LinkFinder, SecretFinder), continuous monitoring (new subdomain alerts, JS change detection, GitHub commit watch). Use when starting recon on any web2 target or when asked about asset discovery, subdomain enum, or attack surface mapping.

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。

Web2 recon pipeline — subdomain enumeration (subfinder, Chaos API, assetfinder), live host discovery (dnsx, httpx), URL crawling (katana, waybackurls, gau), directory fuzzing (ffuf), JS analysis (LinkFinder, SecretFinder), continuous monitoring (new subdomain alerts, JS change detection, GitHub commit watch). Use when starting recon on any web2 target or when asked about asset discovery, subdomain enum, or attack surface mapping.

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。

Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing, image/video forensics, chronolocation. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, tracing crypto flows, geolocating media, or performing attribution work.

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。

Okta-as-IdP red-team attack chain — tenant discovery, user enumeration (multiple vectors), authentication flow analysis (factors enumeration, push-notification fatigue, SMS bypass), password spray with lockout discipline, Okta-specific phishing primitives (kits, FastPass abuse, OIDC redirect_uri tampering), MFA enumeration, post-compromise admin API surface. Many enterprise orgs use Okta instead of (or alongside) Entra ID. Distinct endpoints, distinct rate-limiting, distinct factor flows. Use when recon shows `<tenant>.okta.com`, `<tenant>.okta-emea.com`, `<tenant>.oktapreview.com`, or autodiscover-style records pointing at Okta IdP.

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。

Hunt source code and build artifact leakage — JavaScript source maps (.js.map) reconstructing TypeScript/ES6 source, Swagger/OpenAPI JSON endpoint discovery, .env/.git exposure, webpack chunks with hardcoded secrets, robots.txt/security.txt recon, build-info files, asset-manifest.json API route discovery, .DS_Store file listing. Use at the START of every recon session — these findings often unlock the entire attack surface.

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。

Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.

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。

Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.

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。

Inspect Open-Science's JavaScript control REPL, discover managed Project files, Sessions, and Agent Frames, and safely feature-gate host.* calls with host.capabilities(). Use when an Agent needs to discover available host APIs, locate an Artifact or Upload Version, diagnose a Session, or read a Frame transcript in the current Project.

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。

Multi-AI research using available external providers (Double Diamond Discover phase)

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。

Image SEO audit — make a site's images discoverable in Google Images and stop them from dragging down Core Web Vitals. Audits alt text quality and coverage, descriptive file names, modern formats (WebP/AVIF), dimensions and compression, responsive srcset, lazy-loading, explicit width/height (CLS), image sitemaps, and ImageObject structured data. Use this skill whenever the user asks about image SEO, alt text, Google Images ranking, image optimization for search, image file size hurting page speed, WebP/AVIF, or image structured data. Trigger on: "image SEO", "alt text", "rank in Google Images", "optimize my images for search", "image alt tags", "WebP", "image compression SEO", "image sitemap", "ImageObject schema", or any image-discoverability / image-performance question. For overall page speed use /seo-analysis; for generating new images use the brand image skills.

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。