Read information from the screen using AI and return it as a string
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。
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概要と使いどころ
Read information from the screen using AI and return it as a string
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。
Evaluate design effectiveness from a UX perspective. Assesses visual hierarchy, information architecture, emotional resonance, and overall design quality with actionable feedback.
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 the web, read source pages, and retrieve structured records with Firecrawl. Use for current information, finding sources, reading a supplied URL, or looking up data-provider capabilities.
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。
Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".
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。
将文章内容自动拆分为多张信息图海报(2400x3600竖版),支持多种风格模板和6种页面布局。 Use when: (1) 用户说"生成海报", (2) 用户发文章要求做图, (3) 用户说"做成卡片/信息图" (4) 用户发文章并希望转成可分享的图片, (5) 用户要求制作信息图/infographic
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。
Maxim Master Design Intelligence — full-spectrum UI/UX orchestration. Activates all design sub-domain skills in parallel. Use when a task spans multiple design domains simultaneously: product design strategy, interaction design, information architecture, usability heuristics, design critique, cross-platform consistency, design leadership. The master conductor of all Maxim design agents.
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 design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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 three-surface marketing system organized around alternating black, white, and PlayStation Blue chapters that scroll past the viewer like a console launch trailer. Each section has a single editorial purpose — hero photography, console product render, PS Plus tier callout, news strip — and each owns one of three full-bleed canvas modes. The chrome is unusually quiet for a gaming brand: bright PlayStation Blue (`#0070d1`) carries every primary CTA as a fully-rounded pill, the proprietary SST face renders display copy at a signature weight 300 (light) for an airy, premium feel, and a crisp 8px-radius secondary card system carries product info on either canvas mode. The system never decorates — no gradient backgrounds on chrome, no atmospheric mesh, no drop shadows beyond a faint section-divide. Imagery does all the heavy lifting: console glamour shots, game key art, and PS Plus tier illustrations occupy 60-90% of every section, with copy compressed into a small editorial slot.
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。
.NET / C# 二进制逆向。当目标是 .NET assembly(PE 头含 CLR、.exe/.dll 托管程序)、C# 编译产物(含 NativeAOT)、红队 Sharp* 工具(Rubeus / SharpHound / SharpHound 等)、.NET 混淆程序(ConfuserEx / SmartAssembly / Babel / Eazfuscator)、.NET loader / info-stealer / 套壳 malware 时使用。优先用 dnSpyEx + de4dot,需要 AI 直接操作时联动 dnSpy MCP。不用于纯 native 二进制(走 reverse-engineering / ida-reverse)。
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。
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
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 the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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。
Write outbound promotional copy for a product or project: launch and update posts for community platforms and social media, store page descriptions and short blurbs, landing page headlines and calls to action, press-style announcements, and the naming of a product for another language or market. Covers what may be disclosed publicly, keeping claims traceable to shipped changes, and writing a headline that carries information instead of hype. Use when drafting or revising anything aimed at people who do not use the product yet, and when deciding whether a link, key, price, or unreleased detail can appear in public copy.
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。
Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.
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。
Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.
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。
Think and work like an expert Mathematical Modeler. Use when a task calls for Mathematical Modeler judgment. Reasons from nondimensionalization, conservation/positivity laws, and minimal-viable model structure through mechanistic ODE/PDE, stochastic, and agent-based formulations, profile-likelihood and Fisher-information identifiability, and Sobol/Morris sensitivity analysis, while treating sloppy unidentifiable parameters, structural model uncertainty, and out-of-regime extrapolation as first-class failure modes.
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。
Think and work like an expert Industrial Ecologist. Use when a task calls for Industrial Ecologist judgment. Reasons from mass balance closure, in-use stocks, and system boundaries through STAN (ÖNorm S 2096), dynamic MFA with Weibull lifetime distributions, EEIO tables (EXIOBASE, USEEIO) and pedigree-scored Monte Carlo while treating non-closing residuals, re-export trade hubs, downcounted informal-sector leakage, and Kalundborg-copied symbiosis without quality-spec match as first-class failure modes.
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。
Think and work like an expert Developmental Psychologist. Use when a task calls for Developmental Psychologist judgment. Reasons from developmental trajectories, measurement invariance, and familial-environmental context through age-normed instruments (Bayley, WPPSI/WISC, CBCL, MacArthur-Bates CDI), false-belief and violation-of-expectation paradigms, and lme4/lavaan growth models while treating verbal-demand confounding of theory of mind, informative attrition, adult-normed task misapplication, and parent-versus-direct-assessment divergence as first-class failure modes.
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。
Think and work like an expert Developmental Biologist. Use when a task calls for Developmental Biologist judgment. Reasons from stage, positional information, gene regulatory networks, and tissue mechanics through morphology-based staging (Carnegie/HH/Theiler/NF/hpf), French-flag morphogen logic, light-sheet 4D imaging, lineage tracing, and ARRIVE/MDAR/REMBI reporting while treating developmental delay, CRISPR F0 mosaicism, morpholino p53 toxicity, and conflated fate-versus-lineage claims as first-class failure modes.
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。
Manage the operational learnings lifecycle — load prior learnings to inform current work, harvest new patterns worth preserving, and keep the document tight over time. Provides a protocol for accumulating actionable patterns from practice that complement standards and defaults. Use when a workflow session completes and produced insights worth persisting, when starting a session that should benefit from prior patterns, or when the user says 'harvest learnings', 'what have we learned', 'capture this pattern', 'tighten learnings', 'compress learnings', or 'operational learnings'.
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。
Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.
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。
Provider-independent ecommerce product imagery production for marketplace listings, product pages, hero shots, lifestyle scenes, comparison charts, infographics, variant/packaging images, virtual try-on or placement mockups, ads, and AI-assisted product visuals. Use when an agent must plan, generate, edit, review, localize, package, or QA truthful commercial product images while managing SKU continuity, marketplace requirements, claims, rights, releases, accessibility, and approval.
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。
Research potential leads with verified contact information, professional backgrounds, company context, and social presence. Combines LinkedIn profiling, email verification, company enrichment, and social signals for sales-ready prospect intelligence.
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。
Extract and analyze pricing information from competitor websites. Identifies pricing tiers, features per tier, billing models, and positioning relative to market alternatives. Ideal for competitive pricing strategy and market positioning research.
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。
Build targeted outreach lists with verified contact information, professional context, and conversation starters. Combines Apollo company data, LinkedIn profiling, and email verification to produce ready-to-send outreach campaigns for sales, PR, and partnership teams.
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。