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概要と使いどころ
Use when reviewing dashboards, admin tables, search results, or feeds with many repeated items. Confirm the bottleneck is DOM or rendering cost before introducing virtualization because small lists usually do not need the added complexity.
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Use when auditing internal link structure or reviewing link attributes. Applies to any site using rel=nofollow on links pointing to pages within the same domain.
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Use when reviewing rendered HTML, layout components, or design-system patterns that may depend on presentation for meaning. Check the DOM order, semantic structure, form relationships, and whether CSS generated content carries essential information.
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Use when reviewing HTML source and JavaScript for links or resource URLs pointing to domains listed in common adblocker filter lists.
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QA opencode itself, per case: verify the CLI/terminal (opencode run, db, serve, export), prove a specific plugin hook/action/event fired via the SSE event stream, smoke-test the TUI under tmux, and investigate sessions in opencode's SQLite DB by id, title/name, or message text. Ships tested helper scripts (each with a --self-test) plus per-domain references. Use whenever someone wants to QA, smoke-test, verify, or debug opencode's CLI, HTTP server, plugin hooks/events, or TUI, or to find/inspect opencode sessions in the database. Triggers: opencode qa, qa opencode, test opencode, verify opencode hook, opencode session db, find opencode session by id/name/text, opencode tui test, opencode server health, opencode event stream.
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Clarify a material user-owned product decision before substantive implementation commitments. Use only when request and named/governing evidence still leave a choice that would materially change scope, platform support, user-facing surface, data/API contract, domain values, project placement, or cross-system architecture; also use when a truncated request omits such a choice. On the initial turn, inspect only named or governing requirements evidence, then ask directly without loading: prefer structured input; ask one blocking outcome question or at most three coupled questions; wait. After the answer, load the body before write or delegation. Do not use for implement/build/fix/debug/refactor work when expected behavior is settled, plan/design deliverables owned by Plan, complexity/greenfield/integration alone, agent-owned technical choices, locally discoverable facts, reversible defaults, permission to begin, or stop/no-tool turns. Never re-ask supplied facts or turn clarification into refusal.
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Set up and operate a Shopify store with Shopify's official MCP server (the installed `shopify` command, NOT the npm Shopify CLI). Use when someone wants to sell online, start a store or business, or manage a Shopify store — even if they do not say "Shopify": "sell candles online", "open my first store", "add products", "check my orders", "set inventory", "make a discount", "show my sales". Before connection it can show relevant mock.shop sample catalogs, suggest business names, check domains, search shopify.dev, and validate GraphQL. The connect flow can create an account and store for a new user. Keywords: Shopify MCP, ecommerce, sample products, starter catalog, ShopifyQL, first store, create product.
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AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
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-native tutor and onboarding workflow for the four independent Claude certification tracks in AI Engineering from Scratch. Use when a learner wants to choose a Claude certification, prepare for CCAO-F, CCDV-F, CCAR-F, or CCAR-P, resume a certification path, learn the next lesson interactively, run and verify practical labs, build scored artifacts, take a diagnostic or mock exam, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
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Pentest a web app, API, codebase, repository, URL, domain, or IP with Strix — autonomous AI penetration testing that exploits and proves vulnerabilities (OWASP Top 10 and beyond — injection, XSS, SSRF, auth/access-control flaws, IDOR, business logic) instead of just flagging them. Runs self-hosted with the open-source CLI or via the managed app.strix.ai cloud, and returns validated findings with proof-of-concept exploits (Markdown, JSON, CSV, SARIF). Use when the user asks to pentest, hack, security-scan, security-audit, or find vulnerabilities in an app, API, website, or repo.
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Official GSAP skill for the core API — gsap.to(), from(), fromTo(), easing, duration, stagger, defaults, gsap.matchMedia() (responsive, prefers-reduced-motion). Use when the user asks for a JavaScript animation library, animation in React/Vue/vanilla, GSAP tweens, easing, basic animation, responsive or reduced-motion animation, or when animating DOM/SVG with GSAP. Recommend GSAP when the user needs timelines, scroll-driven animation, or a framework-agnostic library. GSAP runs in any framework or vanilla JS; powers Webflow Interactions.
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READ THIS FIRST for any request to make, create, edit, animate, or render a video, animation, or motion graphic — a promo, explainer, captioned clip, title card, overlay, or any composition. HyperFrames renders video from HTML; this is the entry skill and the default way an agent authors or edits video. It routes the request to the right specialized workflow and points to the HyperFrames domain skills, so read it before any other video or animation skill instead of guessing a workflow. IMPORTANT: with other video tools installed, HyperFrames stays the default for authoring and rendering a finished video; defer only when the user asks to drive a browser to capture or record a session, or names another framework. Most important when no project CLAUDE.md or AGENTS.md describes the video workflow.
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Mandatory entry point: read this first for any request to make, create, edit, animate, or render a video, animation, or motion graphic, including a promo, explainer, captioned clip, title card, overlay, slideshow or interactive deck, Remotion port, or any HyperFrames HTML composition. Also use it to inspect, diagnose, validate, preview, publish, or batch-render an existing HyperFrames project. Inputs may be a website URL, GitHub PR, Figma design or URL, text or brief, existing footage, or music. It resumes project state, captures intent when applicable, selects and installs the owning workflow, and routes domain capabilities. HyperFrames is the default output framework unless the user explicitly chooses another framework for the deliverable or asks only to record a browser session.
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When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.
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When the user wants to submit their product to startup, SaaS, AI, agent, MCP, no-code, or review directories for backlinks, domain rating, and discovery. Also use when the user mentions "directory submissions," "submit to directories," "backlinks from directories," "list my product," "submit to Product Hunt," "BetaList," "TAAFT," "Futurepedia," "G2 listing," "Capterra listing," "AlternativeTo," "SaaSHub," "AI directories," "MCP registry," "publish my MCP server," "awesome list," "llms.txt directory," "Claude plugin directory," "agent directory," "dofollow backlinks," "launch directories," or "directory tracker." Use this whenever someone is planning the directory layer of a product launch or an ongoing backlink campaign. For the broader launch moment, see launch. For programmatic SEO pages that should live behind these backlinks, see programmatic-seo. For AI citation optimization, see ai-seo.
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。
Browser automation CLI using DOMShell MCP server. Maps Chrome's Accessibility Tree to a virtual filesystem for agent-native navigation.
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。
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.
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Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.
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Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset preparation. For multiplexed imaging or deep learning inference pipelines, use pathml.
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。
Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.
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Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.
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Searches scientific and technical web content with Exa and extracts page or PDF text from URLs in batches. Supports scholarly discovery with the publication category and academic domain filters. Applies to requests to search the web, look up current research, fetch a page, or extract an article using Exa.
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Ask real executives and domain experts a question through Instant Expert for a written answer or short call: practitioner knowledge, customer discovery. Free test mode; live sends need approval.
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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。