「each」の検索結果

Expert LGPD compliance advisor for Brazil's Lei Geral de Proteção de Dados (Law 13,709/2018). Use this skill whenever a user asks about LGPD, Brazilian data protection, ANPD, personal data processing in Brazil, data subject rights under Brazilian law, legal bases for processing, sensitive data handling, DPO appointment in Brazil, data breach notification to ANPD, LGPD penalties (fines up to 2% of revenue / R$50M), international data transfers from Brazil, Brazil-EU mutual adequacy (January 2026 — SCCs/BCRs no longer needed for Brazil-EU transfers), LGPD gap assessments, privacy policy drafting for Brazilian operations, DPIA under LGPD, consent management, or comparing LGPD with GDPR. Trigger for any Brazil privacy or data protection question even if LGPD is not named 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。

Code-drawn stills, drawing timelapses, films, explainers and interactive web animations in 32 styles, with composed scores. Matches a reference style, keeps characters consistent, teaches drawing. Deterministic, no generated assets.

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。

Attach/install/use clawhip as a daemon-first notification gateway runtime for OpenClaw / Clawdbot

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, inspect, and safely update project-scoped ReachAI Agents; edit and publish Supervisor config drafts; discover published bindable Skills; and attach or detach exact Skill versions through the Agent AI Coding REST API. Use when an AI coding tool is asked to add an Agent, configure its model or prompt, bind a Skill, remove a Skill binding, or attach a published Workflow as a Tool.

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, validate, debug, publish, and inspect ReachAI Workflow drafts through the Workflow AI Coding REST API. Use when asked to create or modify a workflow graph, add/update/delete nodes or edges, validate GraphSpec, dry-run or debug-run a workflow, inspect trace/run output, check release readiness, publish a validated draft, or work on PAGE_ASSISTANT workflows from Cursor/Codex.

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 critique with 7 rated passes: Information Architecture, Interaction State Coverage, User Journey and Emotional Arc, AI Slop Risk (10-item blacklist), Design System Alignment, Responsive and Accessibility, Unresolved Decisions. Each rated 0-10 with gap-fill loop. Parallel cross-model design voices.

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。

Generates code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.

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。

Diagnose performance issues on Amazon SageMaker HyperPod clusters — uneven NCCL bandwidth across nodes and poor filesystem throughput. Read-only. Surfaces host-side signals (Xid, ECC, NVLink, EFA reachability, FSx saturation) and routes to the appropriate sibling skill (hyperpod-node-debugger, hyperpod-nccl, hyperpod-version-checker, hyperpod-issue-report) for any remediation. Triggers on uneven NCCL across nodes, straggler node, FSx slow, checkpoint slow, dataloader slow, filesystem bottleneck, FSx throughput, cross-AZ latency, topology mismatch.

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 a paid media plan: channel split, weekly flighting, audiences, reach and frequency. "plan our Q4 ad budget"

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 integrations status: connected and available connectors, what each unlocks. "which connectors do I have"

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。

Detect growth loops in the business and model each loop's amplification by script. "what growth loops do we have"

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 ad copy variants to each platform's specs, policy-checked and in brand voice. "write ad copy for Meta"

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 has nothing — no traces, no labels, no eval set — and needs to build a v0 evaluation from scratch. Also use when the user says "I need to start evaluating my app but don't know where to begin," "I want to set up eval for a new product," or has just identified failure modes and needs to turn them into principles. Outputs a v0 grader in 30 minutes using OpenJudge SimpleRubricsGenerator, plus a roadmap to reach calibrated evaluation.

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。

Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.

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).

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。

When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," or "fCMO plan." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a full marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.

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 multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant 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。

Generate scaffolds that gradually increase student choice, voice, and ownership within a learning task. Use when students depend heavily on teacher direction and need to develop autonomy.

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。

Generate structured reflection prompts for a specific teaching experience or professional learning challenge. Use when debriefing lessons, journaling, or preparing for coaching conversations.

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 a professional development session using adult learning principles with active teacher engagement. Use when planning INSET days, CPD workshops, or staff training sessions.

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。

Develop TPACK for integrating a specific technology or AI tool into subject teaching with pedagogical alignment. Use when adopting new ed-tech, reviewing AI tools, or planning technology integration.

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。

Translate an external competency framework like DigComp, GreenComp, or ISTE into classroom-ready activities. Use when implementing framework standards in specific teaching contexts.

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 a single-point rubric with one criterion and open columns for evidence. Use for student self-assessment, peer feedback, teacher formative feedback, or pre-task planning. Works with any learning target, with or without a band system.

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。