「clarify」の検索結果

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

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。

When the user wants to plan integrated marketing, coordinate channels, or clarify program vs channel vs campaign. Also use when the user mentions "IMC," "integrated marketing," "channel mix," "marketing program," "PESO model," "integrated marketing communications," "omnichannel marketing," "channel strategy," "marketing mix," or "cross-channel campaign." For content planning, use content-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。

Modern, interactive alternative to `/do` — clarify intent up front, then take a task end-to-end with a serial AI review gauntlet (lens debate (lowy ⇄ hickey) → codex debate → simplify → code-police, each editing the branch in turn) → CI → evidence. ONLY invoke when the user explicitly types `/be` or `$be`; never auto-select from a natural-language request.

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。

Clarify a new customer brief, desired outcome, constraints and evidence gaps. Use for kickoff or a first meeting; do not repeat discovery already supplied.

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 mathematically, empirically, or technically dense papers for readers outside the author’s specialty, including empirical legal scholarship, law-and-economics models, and legal-technology research. Clarifies terminology, antecedents, study design, and claim–statistic relationships while checking equations, numbers, quotations, and citations against the source. Use to clarify exposition or de-jargonize a technical draft; not to rewrite briefs or doctrinal arguments. Produces an edited draft and audit memo. Full integrity checks and original-format rendering require suitable extraction, code execution, and document tools; otherwise provides proposed edits with verification limits disclosed.

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 this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.

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 - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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 in a loopkit-enabled project - establishes how to find and use loopkit's 49 skills, requiring skill invocation before ANY response including clarifying questions.

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 - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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。

Clarify domain concepts, language, boundaries, and durable architectural decisions. Use when terminology is ambiguous, the user is shaping a domain model, or a design depends on resolving what concepts mean.

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。

Clarify a decision one question at a time and compare options against explicit criteria. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.

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 - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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。

Adapts an existing K-12 lesson (math, ELA, science, or social studies) for students at different proficiency levels (below / at / above grade level). Load this skill BEFORE asking the teacher any clarifying question about the lesson, tiers, or student levels. Triggers on explicit asks to differentiate, tier, or scaffold a lesson, and on implicit signals like "my students are at different levels". Produces 1 teacher-facing differentiation plan + 3 student-ready tier documents as editable Word documents in a single output turn, rendered from one material-source JSON via bundled scripts (shared content is written once so tiers cannot drift). Uses the Learning Commons Knowledge Graph when connected; works without it. This skill adapts a lesson the teacher brings or names. Not for creating a new lesson from scratch — a new-lesson request that asks for differentiated or leveled materials is k12-lesson-plan-creation's job, one package. Not for grading, rubrics, assessment feedback, or quizzes.

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。

Creates a lesson plan, student-facing materials, and observation template. Load this skill BEFORE asking the teacher any clarifying question about grade, subject, topic, standard, or timing. Use when a K-12 teacher needs a math, ELA, science, or social studies lesson built from scratch — even if grade, subject, or topic isn't yet stated. Do NOT load for grading, a rubric, assessment feedback, a quiz, or a standards lookup — answer those directly. Triggers on explicit requests (lesson plan, mini-lesson, unit plan, daily plan) and implicit teacher intent: "I'm teaching long division to 5th graders," "need to teach photosynthesis tomorrow." Core signal: teacher needs new instructional content created. A new lesson that asks for differentiated, tiered, or leveled materials is still ONE planning request — this skill produces those materials inside the lesson package; do not also invoke k12-lesson-differentiation. Not for differentiating an existing lesson (use k12-lesson-differentiation) or passage rewrites.

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。

Creates a Check for Understanding (CFU) for a math topic or standard: 1–3 targeted formative items whose distractors come from documented student misconceptions, plus a teacher guide routing each likely response to a specific next instructional step. Load BEFORE asking any clarifying question about grade, standard, or topic. This skill is for math; for other subjects, help as you normally would and don't mention the skill to the user. Triggers on asks to create, write, generate, or design a check for understanding, formative check, quick check, or exit ticket for a math concept or standard, and on implicit signals like "I need to see who got it before I move on." Not a quiz, test, or practice set — a CFU is read for what it reveals, not scored, so a numbered quiz or a bare answer key is a different job. Does not create a lesson (k12-lesson-plan-creation, which brings its own exit ticket), tier one (k12-lesson-differentiation), or prepare a teacher to teach one (k12-lesson-prep).

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。

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

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。

Guide a feature implementation through a structured seven-phase workflow with deep codebase understanding, clarifying questions, parallel architecture design, and quality review. Use this skill when the user asks to build a new feature, add functionality, or wants a methodical approach to implementation rather than diving straight to code.

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。

Structured requirements elicitation for analysis requests. Use when scoping new analysis projects, clarifying ambiguous business questions, or documenting analysis acceptance criteria with stakeholders.

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。

SkillAlchemy — One thought conceived, one goal achieved. Accept any idea or distillation target and produce an installable SKILL.md. It uses Lens to clarify the problem and LEAP to run distillation or fusion. This is the sole user-facing entry point. Use when the user asks to distill, generate a skill, fuse skills, or says, "I want to build X, but I do not know where to start."

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。

Interpret third-party feedback by running parallel internal and peer interpretations to surface intent, correctness concerns, and ambiguities. Use when the user asks to "interpret feedback", "interpret comments", "what does this feedback mean", "clarify reviewer intent", "understand this review", or "interpret these suggestions".

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。

当用户开始新小说项目时激活 - 通过温和的提示和解释引导他们完成七步方法论（constitution → specify → clarify → plan → tasks → write → analyze）

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。

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

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 offensive-security engagement or task — establishes how to find and invoke the right skill before any action (including clarifying questions, recon, exploitation, or reporting)

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。