3,156 件 ・ 関連度順
概要と使いどころ
Check AI-generated marketing content and reviews for required disclosures under the EU AI Act, FTC rules and platform AI-label policies. Use when labelling AI ads, deepfakes, chatbots, influencer posts or testimonials.
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。
Transform AI-generated content into human-sounding writing via AI pattern detection, rhythm restoration, and authenticity scoring. Use when content sounds robotic, uses AI cliches, or the user wants to humanize or fix AI writing.
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。
Personal leadership development for founders and first-time CEOs. Use when a founder feels like the bottleneck, struggles to delegate, is burning out, or transitioning from IC to executive.
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Migrate Terraform provider resources and data sources from Plugin SDKv2 to the Plugin Framework: muxing both plugins in one provider (terraform-plugin-mux, tf5to6server), per-resource migration workflow, SDKv2-to-Framework schema mapping (ForceNew, ValidateFunc, DiffSuppressFunc, Default, Timeouts, blocks), null-vs-zero-value behavioral traps, and state-compatibility verification. Use when converting or translating SDKv2 resources to the Framework, setting up a muxed provider server, deciding whether a resource should be migrated at all, or debugging plan diffs and state errors that appeared after a migration.
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 processing skill for cropping images to 50% from center and rotating them 90 degrees clockwise. This skill should be used when users request image cropping to center, image rotation, or both operations combined on image files.
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。
Audit or generate XML sitemaps: limits, lastmod, status codes, robots conflicts. "audit our sitemap"
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。
Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools
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World-class prompt powerhouse that generates production-ready mega-prompts for any role, industry, and task through intelligent 7-question flow, 69 comprehensive presets across 15 professional domains (technical, business, creative, legal, finance, HR, design, customer, executive, manufacturing, R&D, regulatory, specialized-technical, research, creative-media), multiple output formats (XML/Claude/ChatGPT/Gemini), quality validation gates, and contextual best practices from OpenAI/Anthropic/Google. Supports both core and advanced modes with testing scenarios and prompt variations.
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 writing Agent Relay or Ricky workflows that must loop review, fix, and validation with fresh agent context until independent signoff agents, typically Claude and Codex, both agree the work is comprehensively complete. Covers fresh-context iterations, repairable gates, dual reviewer verdict contracts, iteration-count reporting, PR signoff comments, and blocked-state handling.
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 fable-mode execution discipline on Claude Haiku. Routes the task to the @fable-worker-haiku agent, whose definition carries the staged loop with tightened verification (no bare "unverified" allowed) and an escalate-don't-improvise rule. Trigger when the user explicitly asks for thorough/systematic handling run cheaply or fast ("fable on haiku", "deep work mode but cheap", "stage this on haiku"). For bulk mechanical work. Do NOT use for tasks needing synthesis — benchmark note: at n=1 the skill's effect on Haiku swung both directions (+25 / −17); route quality-critical work to fable-sonnet instead.
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。
Production-grade web scraping with automatic anti-bot bypass, structured JSON parsing for 40+ targets, and geo-targeting. Use when the user needs to scrape web pages, extract product data, get search results, or collect structured data from supported e-commerce and search platforms without worrying about getting blocked and when geo targeting is required.
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Connects to Oxylabs remote agent browsers over the Chrome DevTools Protocol (CDP) with Playwright or Puppeteer. Built-in anti-detection, residential proxies, geo-targeting, persistent sessions and profiles, session recording and live VNC inspection for debugging. Use instead of WebFetch or a local browser whenever a site renders with JavaScript, blocks bots (DataDome, Cloudflare, Akamai), needs a real browser session, screenshots or PDFs. Covers connection, retries, error recovery and safe scraping of protected targets without any human help.
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When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
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。
An animated bottom-tab indicator — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.
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。
A toast slides up from the bottom, holds, then fades away. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A bottom tab bar whose active pill slides between tabs. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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 original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit criteria pass. Do not use merely to summarize an existing packet or to advise parties in a real dispute. Requires local file access; Python 3 is recommended for bundled deterministic checks, with disclosed manual fallbacks when unavailable.
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Evaluate completed mediation-competition problems consisting of general information and confidential packets for both sides. Use when asked to validate, audit, score, quality-control, or assess competition readiness; identify factual, numerical, chronological, authority, commercial-logic, or confidentiality defects; test mediation usefulness, BATNAs, settlement corridors, information asymmetry, and opportunities for firmness, cooperation, imagination, and clarification; or produce an author-only validation report. Perform a qualified partial review when packets are missing. Diagnose by default; do not generate a new problem or edit source packets unless repairs are expressly requested. Requires access to all supplied files and a host capable of reading their formats; otherwise disclose the unreviewed material and resulting limits.
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。
Apply elite legal writing techniques drawn from Justice Kagan, Boies & Olson, and other top advocates to any legal document — briefs, submissions, letters, opinions, memos, or persuasive correspondence. This skill covers both prose craft (clarity, examples, parallel construction, voice, quoting) and architectural strategy (argument sequencing, framing, openings, endings). Use this skill whenever the user asks you to draft, edit, or improve legal writing and wants it to be genuinely persuasive — not just correct. Also trigger when the user mentions 'make it more persuasive', 'sharpen this', 'strengthen the argument', 'rewrite this section', 'punch it up', 'legal writing', 'draft a brief', 'draft a submission', 'write like a top advocate', or asks you to improve the rhetoric, flow, or force of any legal document. This skill complements the larissa-legal-voice skill (which handles tone and personal voice) by adding the persuasive technique layer on top.
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。
Rigorous multi-pass editor for law review articles, student notes, seminar papers and other legal scholarship. Runs six specialized passes — structure, substantive critique, Bluebook citations, grammar and clarity, fact-checking against sources, and a synthesizing memo — and delivers an editorial memo with issues prioritized as critical, substantial or minor and keyed to specific footnotes and paragraphs. Handles articles of any length, including 50,000-word pieces, by chunking on section boundaries. Reads .docx directly. Use when editing, critiquing, workshopping or pre-submission-reviewing academic legal writing. Triggers on "edit my article," "review this draft," "critique my note," "check my Bluebook citations," "is my argument sound," "read my law review piece," "workshop this paper," "pre-submission review." Chunking needs Python 3; fact-checking needs web search; both degrade gracefully without.
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。
EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus adopted June 29, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of July 2026. GPAI enforcement powers activate August 2, 2026.
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。
Assesses which of the Art. 50(1)-(5) transparency obligations of the EU AI Act apply to a given AI system's provider or deployer, grounded in the final Code of Practice on Transparency of AI-Generated Content (June 2026) and the Commission's draft Art. 50 Guidelines. Covers AI-chatbot disclosure, deepfake and synthetic-content marking/watermarking, emotion-recognition and biometric-categorisation notices, the machine-readable marking duty, the obviousness exceptions, and the implementation timeline. Outputs a formal mini-report plus a per-obligation compliance checklist with gap flags. For breadth-first tier triage use the EU AI Act System Classifier; for raw Art. 50 text and Q&A use the EU AI Act Knowledge Base; for the full role x tier matrix use the EU AI Act Obligations Mapper.
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。
Adversarially stress-tests a legal text — a contract, statute, regulation, or judicial opinion — for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA — even if the user never says "stress-test" or "ambiguity."
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。
Matter budgeting and ongoing WIP/variance monitoring. Build phase-based fee estimates at matter setup, run bottom-up budgets by jurisdiction or workstream, calculate contingency, and structure AFA arrangements (fixed fee, capped fee, phased fixed fees). Ongoing monitoring: WIP tracking against budget, proportionality assessment (spend vs progress), variance commentary with root cause analysis, forecast-to-complete, realisation monitoring, write-off analysis. Trigger on: 'build a budget', 'fee estimate', 'what will this cost', 'WIP review', 'budget vs actual', 'how are we tracking against budget', 'we're over budget', 'realisation is poor', 'what's our ETC', 'budget for the German workstream', 'model the financial impact of this scope change', 'draft a fee adjustment', 'write-off analysis', 'how much contingency', 'AFA structure', 'fixed fee estimate', 'budget update', 'forecast to complete'.
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。