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概要と使いどころ
Check that a web page you wrote or changed actually works, by opening it in a browser and driving every control on it. Use after creating or editing an HTML page, or the JavaScript or CSS that a page loads.
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 the user wants to pull data out of one or more PDFs (invoices, bank/credit-card statements, receipts, reports, tables) and put it into a spreadsheet. pdf_read is one of the most-used tools; this codifies the read-PDF → structure → write-Excel workflow. Powered by LMCP on macOS and Windows.
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 whenever the task involves inspecting, modifying, or building plugins for Bethesda games via the forked xEdit automation daemon. Loads first; routes to the right path (MCP intent tool, MCP atomic passthrough, or sub-agent delegation) and prevents the agent from bypassing the harness.
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 Experience Optimization: reads Google SERPs backwards to detect page-type mismatches, derives user stories from search intent signals, and scores pages from multiple persona perspectives. Identifies why well-optimized pages fail to rank by analyzing what Google rewards for each keyword. Use when user says "SXO", "search experience", "page type mismatch", "SERP analysis", "user story", "persona scoring", "why isn't my page ranking", "intent mismatch", or "wireframe".
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。
E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace intelligence, product schema validation, competitor pricing analysis, and marketplace keyword gaps. Combines on-page product SEO with marketplace data from DataForSEO Merchant API. Use when user says "ecommerce SEO", "product SEO", "Google Shopping", "marketplace SEO", "product schema", "Amazon SEO", "product listings", "shopping ads", or "merchant 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。
Use when starting ANY conversation involving Bethesda Game Studio modding, MO2, xEdit, or modpack curation. Bootstrap that loads the toolkit overview, lists available task skills, and enforces the hard rules of this plugin. Auto-injected by the OpenCode plugin's chat.messages.transform hook and by the hooks/ session-start chain in Claude Code and Codex.
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 future work, investigate before building, research a topic, or compare the alternatives for a choice. Takes optional free text. The skill reads the request, open drafts, accepted canon, branch, and code, then creates only the documents a later reader needs — none for a small fix. Use for 'plan the X redesign', 'create a roadmap', 'plan a new feature', 'plan the onboarding journey', 'investigate X before we plan', 'compare the alternatives for Y', 'REST or a queue? two teams disagree', 'I need market research before we plan', 'we are regulated — trace the requirements'. With no arguments it resumes an open planning draft or offers what to plan next. Not for recording a decision or documenting existing code — use /archcore:document. Not for checking docs against code — use /archcore: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。
Explicit landing-page build and deploy operator. Loads marketing and frontend judgment, scaffolds the smallest suitable site, verifies it rendered, deploys to the configured target.
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。
Send cold email and run outbound email campaigns from an agent with Sendsets. Connect or check sending mailboxes, turn a lead list (CSV or inline) into a multi-step email sequence with follow-ups, validate merge fields, send a test, launch, and read and answer replies. Use when the user asks to send cold emails, email a list of prospects or leads, run an outreach or outbound sequence, or follow up with contacts by email.
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 platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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。
Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.
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。
Anti-slop skill for PRODUCT UI - dashboards, data tables, forms, multi-step flows, settings, list/detail, app shells. The agent reads the surface, budgets the frame first, and ships dense interfaces that are correct at every edge case (overflow, long labels, empty/error/loading states, i18n expansion, keyboard/a11y). House-system-first; maps to Carbon/Polaris/Atlaskit/Fluent/Primer/Material3/Radix-shadcn/Ant. The counterpart to taste-skill, which owns landing/portfolio/marketing.
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。
Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
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。
Edit drafts into sharper, more human writing while preserving the writer's personal voice, or detect AI-slop patterns without rewriting. Use when the user wants a draft clearer, more direct, more opinionated, or less AI-sounding, or asks whether writing reads as AI. Also the default writing standard for all agent output: 80% ASD-STE100 controlled language plus the format ladder (prose, diagram, HTML page, explainer video).
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。
Edit drafts into sharper, more human writing while preserving the writer's personal voice, or detect AI-slop patterns without rewriting. Use when the user wants a draft clearer, more direct, more opinionated, or less AI-sounding, or asks whether writing reads as AI.
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。
Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
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 drafting or polishing an American Anthropologist (AA) manuscript so it reads across all four fields, follows AA house style (Chicago author-date; free-format submission accepted), fits the section word caps (Research Articles ≤ 8,000 words; abstract 200 words), and uses inclusive, care-ful language. Tightens prose and format; it does not invent content.
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 positioning an American Anthropologist (AA) manuscript against the literature so it reads as a four-field contribution. AA readers span sociocultural, archaeology, biological, and linguistic anthropology, so the paper must engage the conversations they expect and decenter a US/Anglophone-only canon. Stakes the contribution and citational politics; it does not write the lit 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。
Use when anticipating referee objections or calibrating review expectations for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript before submission. Pre-empts the objections theory referees raise and reads the editorial process; it does not draft the response letter (see aejmic-rebuttal).
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 positioning an Agricultural Systems (AgSy) manuscript against the literature so it reads as a systems contribution. AgSy readers span agronomy, modelling, livestock, economics, environment, and food-system science, so the paper must engage the systems and modelling literatures they expect — not only one subfield. Stakes the contribution; it does not write the lit 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。
Use when drafting or polishing an Agricultural Systems (AgSy) manuscript so it reads clearly for a systems-science audience, follows the journal's format, and meets front-matter requirements (abstract <= 250 words, Highlights, graphical abstract). Research papers run to about 8,000 words (no hard cap). Tightens prose and format; it does not invent content.
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 revising an AAMAS paper so the interaction contribution leads the first page, the solution concept or incentive property is named, the game and agents are legible, claims are paired with proofs or multiagent experiments, the argument fits eight two-column pages plus references, and the wording stays double-blind.
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 LinkedIn posts by keywords, sorted by engagement or date. Use when researching what people are saying about a topic on LinkedIn, finding high-engagement content, identifying thought leaders, or discovering warm leads through post engagement. Returns author, post text, reactions, comments, shares, post URL, and date. No LinkedIn cookies or login required.
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。