「writing」の検索結果

When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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。

Rise Big — a composable AnimXYZ entrance via the xyz="fade up-5 big-25%" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Big — a composable AnimXYZ entrance via the xyz="fade big-50%" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Down — a composable AnimXYZ entrance via the xyz="fade down-3" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Flip Up — a composable AnimXYZ entrance via the xyz="fade flip-up-90" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Right — a composable AnimXYZ entrance via the xyz="fade right-3" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Up — a composable AnimXYZ entrance via the xyz="fade up-3" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Small — a composable AnimXYZ entrance via the xyz="fade small-50%" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Fade Left — a composable AnimXYZ entrance via the xyz="fade left-3" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Rotate In — a composable AnimXYZ entrance via the xyz="fade rotate-right-45" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Flip Left — a composable AnimXYZ entrance via the xyz="fade flip-left-90" attribute. Declarative: mix fade + move + scale + rotate without writing keyframes. MIT. Honors 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。

Author learning targets for a competency across developmental bands with precise, observable progression language. Use when writing 'I can' statements for competency-based programmes.

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。

Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.

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。

Script a teacher think-aloud demonstrating expert reasoning processes for a specific task. Use when modelling problem-solving, writing, reading comprehension, or analytical processes.

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。

Unpack a broad standard or competency descriptor into specific, assessable success criteria and sub-skills. Use when interpreting curriculum standards or writing learning objectives.

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。

Classify curriculum content into Know, Understand, and Do categories to align teaching and assessment approaches. Use when planning units, writing objectives, or selecting assessment methods.

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。

Pick the right LLM for CONTRACT DRAFTING — generating, redlining, or rewriting contract language from instructions. Vendor-neutral routing grounded in mid-2026 legal benchmarks (legalbenchmarks.ai Contract Drafting). Asks up to 4 quick questions (cost, speed, accuracy/ stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to draft this clause/agreement", "best AI for drafting contracts", "route this drafting task", or is about to generate/redline contract text and hasn't fixed a model.

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。

Reviews or drafts the agreement that pays an employee to settle their claims — and flags the statutory conditions that decide whether it actually binds them. Works under s.203 ERA 1996 for England & Wales. Flags apparent s.203 condition gaps for a solicitor to confirm (writing, specific complaints, independent adviser, identification, insurance, statement of conditions), drafts the substantive terms (sum, tax characterisation, confidentiality, references, restrictive covenants, indemnities), and surfaces enforceability risks. Does not rule on validity and is not legal advice. Use when the user says 'review this settlement agreement', 'draft a settlement agreement', 'compromise agreement' (old term), or asks whether an agreement is binding.

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。

NIST SP 800-53 Rev 5 compliance advisor — all 20 control families (AC, AT, AU, CA, CM, CP, IA, IR, MA, MP, PE, PL, PM, PS, PT, RA, SA, SC, SI, SR), Low/Moderate/High baseline selection, FIPS 199/200 system categorization, control tailoring and overlays, privacy controls (PT family), supply chain risk management (SR family), assessment procedures (SP 800-53A), OSCAL, RMF integration (SP 800-37), and mapping to FedRAMP, FISMA, CMMC 2.0, and ISO 27001. Use for any federal system security controls, FISMA compliance, RMF step guidance, control narrative writing, or baseline tailoring question.

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。

Expert ISO 27001 compliance assistant for security and compliance teams. Use this skill whenever a user asks about ISO 27001 or ISO/IEC 27001, including any of the following: gap analysis, auditing, compliance assessments, control checklists, policy writing, document generation, Statement of Applicability (SoA), risk assessment, risk registers, risk treatment plans, Annex A controls, ISMS implementation, clause requirements, certification readiness, transitioning from 2013 to 2022, control implementation guidance, incident response policies, access control policies, supplier security, or any information security management system (ISMS) topic. Trigger even if the user doesn't say "skill" — any ISO 27001 or ISMS question should use this skill.

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。

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。

Deconstruct a novel for game adaptation. Compress a raw novel, deconstruction library, or writing project into a SOURCE_BIBLE with cited textual evidence, extracting world rules, player verbs, spaces, character will, systems, and visual anchors — without inventing a genre yet. Use for gameable book analysis, analyze a novel for game adaptation, extract game systems from a book. 游戏化拆书。把原始小说、拆文库或写作工程压缩成有必要原文证据的 SOURCE_BIBLE，提取世界规则、玩家动词、空间、角色意志、系统和视觉锚点，不提前发明游戏类型。用于游戏化拆书、分析小说的游戏改编基础等需求。

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 Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev workflow.

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。