「live」の検索結果

Check live performance KPIs from connected analytics: RAG status, trends, actions. "quick performance snapshot"

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。

Implement approved SEO fixes on a connected CMS, approval-gated. "push the audit fixes live"

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。

Launch an approved multi-channel campaign: blocker checks, then ordered activation. "go live with the campaign"

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。

Import a deliverable template as a reusable placeholder template per brand. "use this proposal structure"

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。

Design an ESP-ready email sequence: subjects, copy, timing, branching, deliverability. "build a welcome sequence"

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。

Show help with live plugin counts: getting started, which skill fits a goal, fixes. "what can this plugin do"

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。

Project ad budget pacing by script from live accounts or given numbers: month-end overspend. "are we overspending this month"

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。

Draft a client proposal or RFP response: scope, deliverables, KPIs, pricing tiers. "respond to this RFP"

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 Fable 5.1 — the top of the escalation ladder and the strongest staged run available. Routes the task to the @fable-orchestrator agent with its model overridden to Fable (`model: "fable"`), which stages the work, delegates artifact production to @fable-worker-sonnet / @fable-worker-haiku, and cold-checks deliverables with @fable-verifier. Trigger when the user explicitly asks for thorough/systematic/"deep work" handling on the strongest model ("fable on fable", "stage this on fable", "deep work mode, fable", "run this on 5.1"), or when a fable-opus run reports the task exceeds Opus's ceiling. Benchmarked 2026-09-02: zero correctness delta on Fable 5.1 at ~1.1× tokens, ~2× wall — a provenance runner, not an accuracy runner. Do NOT use for ordinary single-pass tasks — prefer fable-opus, fable-sonnet, or fable-haiku when the task doesn't need peak reasoning. Fable is plan-included; bulk work still routes down-tier.

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 Sonnet. When invoked by slash command or by name, spawns a Sonnet subagent that follows the staged loop — stage plan, parallel delegation, a failable verification check at each stage, and a skeptical self-review before delivery; a wording-only request runs the loop inline on the current model. Trigger when the user explicitly asks for thorough/systematic/"deep work" handling on Sonnet.

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。

Enforces staged execution discipline on large tasks: a written stage plan, parallel delegation where the runtime supports it, a failable verification check at each stage, and a skeptical self-review before delivery. Trigger when the user explicitly asks OR when the task objectively spans multiple files, sources, or sessions. Do NOT trigger on ordinary multi-step requests that a direct attempt handles fine (autonomous triggering only; explicit invocation always runs).

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Connects to Oxylabs remote agent browsers over the Chrome DevTools Protocol (CDP) with Playwright or Puppeteer. Managed browser environment, 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, serves access challenges, verification interstitials or bot-management block pages, or needs a full browser session, screenshots or PDFs. Covers connection, retries, error recovery, built-in challenge handling (the page_handler parameter, the oxylabs-page-status page state reported by the page handler, manual triggering), telling a handled challenge from a block that needs a fresh identity, and reliable access to publicly available data without manual intervention.

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Words float up and settle as the line enters view — a lively per-word scroll reveal. One or two lines; keep travel modest. Visible instantly under prefers-reduced-motion.

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。

Make a primary button feel alive by gently pulling it toward the cursor as it approaches, then springing back. Keep it subtle and reserve it for one or two primary actions. Disabled on touch and under prefers-reduced-motion. Do not use it on dense UIs full of buttons.

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 stack of cards springs and fans into place on view — a lively hero for a small set (3–5). One set per view. Shown flat/instant under prefers-reduced-motion.

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 a real WebGL / WebGPU / Canvas / shader effect from a live webpage (e.g. an animated gradient mesh, fluid/metaball, gaussian-splat scene, image distortion) and port it to a standalone, dependency-light JS project you can run locally or drop into an HTML artifact. Use when the user points at a site's visual effect and wants to reproduce/port/replay it, especially complex GPU effects our vanilla recipes don't cover.

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。

Redesign a lesson to centre students' cultural backgrounds, community knowledge, and lived experience. Use when making curriculum relevant and inclusive for diverse student populations.

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Predicts access barriers in a learning task before delivery, given a learner variability profile. Distinguishes between barriers addressable through design and those requiring specialist support.

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Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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 an application or system — including one built quickly with AI coding agents — needs a security review with regulatory grounding: a STRIDE threat model, a LINDDUN privacy threat model, a dependency exposure screen against live CVE / CISA-KEV / EPSS data, or a selected, non-exhaustive screen of which EU security obligations (GDPR, NIS2, Cyber Resilience Act, AI Act) may apply and which need determination. Orchestrates the server-enforced threat-modeling workflows of the Ansvar Gateway MCP connector and grounds every regulatory statement in officially published text fetched at answer time — scope, role, and application-date limits stated, never a compliance verdict. Never simulates a workflow and never answers legal questions from model memory.

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Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on conceded facts, wrong-forum objections, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or structured legal reasoning. Triggers on "attack this but only with points that hold", "no cheap shots", "what survives reply", "which points can I actually defend", "give me the version I can file", "double-pass adversarial review". Also use when an earlier adversarial review came back overlong or scattershot. Formal British English.

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GDPR Transfer Impact Assessment for Chapter V transfers under the EDPB Recommendations 01/2020 six-step methodology, the CNIL TIA Guide (January 2025), and EDPB essential guarantees. Handles transfer qualification, Art. 45 adequacy fast-tracks, Art. 46 full assessments with country profiles for 12 jurisdictions, and balanced Art. 49 derogation analysis. Outputs a Markdown report, a .docx formal TIA, and a JSON delta for RoPA interchange.

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Draft GDPR/DSGVO-compliant privacy notices as .docx for any EU/EEA jurisdiction and audience. Use when user asks to create a privacy policy/notice, mentions "Datenschutzerklärung", "politique de confidentialité", "privacy notice", needs Art. 13/14 disclosures, AI Act transparency, cookie policy, or notices for applicants ("Bewerber-Datenschutz"), employees ("Beschäftigten-Datenschutz"), B2B partners, or B2C customers. Covers DE (DSGVO+BDSG+TDDDG), FR (RGPD+LIL+LCEN), AT, IT, ES, NL, BE, IE, UK GDPR. Five notice types: Website/App, Applicant, Employee, Business Partner, B2C Customer.

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。

Turns a legal question, a set of draft questions, or source material such as a statute, jury instruction, rubric, contract checklist, or coding manual into a battery of narrow questions that TypeSafe's Jev, a fast classifier that returns probabilities rather than prose, can answer reliably across many documents. The skill breaks conclusions such as negligence, felony murder, or standing into element-level questions, writes the governing rule into each question, and delivers the questions alone, in Jev's request format or in plain English. Built for legal work that asks the same questions of many texts: coding statutes across jurisdictions, coding opinions or case files for empirical research, checking contracts against a review checklist, screening intake narratives, and grading student work against a rubric. Use when asked to write Jev questions, build a classifier for legal documents, or turn a legal test into yes-or-no questions. Running the questions requires Jev access; writing them does not.

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。