Generate sports trivia questions by sport/era/difficulty. Multiple formats with obscure stats, fun facts, pub quiz ready content.
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
Generate sports trivia questions by sport/era/difficulty. Multiple formats with obscure stats, fun facts, pub quiz ready content.
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 proven sales methodologies (MEDDIC, BANT, Sandler, Challenger, SPIN) across your team. Generate framework-specific questions, score deals, train reps, and enforce consistent qualification. Use when implementing or optimizing sales 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。
Generate pre-call research briefs with company news, stakeholder backgrounds, and custom discovery question sets.
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。
Analyze inbound leads (form fills, demo requests) and score based on ICP fit, intent, and urgency. Auto-generates qualification questions, routes to right rep, and suggests personalized first touch. Use for qualifying and routing inbound leads at scale.
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。
Wire a System One model (Jev, or an open reproduction like Von) into a product feature — routing, guardrails, scoring, classification. Use when replacing an LLM call that returns a label rather than prose, when adding a typed decision to an agent loop, or when deciding between the hosted Jev API and a local open model. Covers question design, the eval-set-first workflow, threshold calibration, confidence gates, and the traps measured on real data.
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。
Optimize job applications by tailoring resumes to job postings, generating customized cover letters, and preparing role-specific interview questions. Analyzes job descriptions to highlight relevant skills and experience. Use when users need to apply for jobs, customize resumes, or prepare for interviews.
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。
Drop a folder of vendor quotes, proposals, and SOWs on Cowork -- normalizes them into one comparison matrix, computes true total cost of ownership, surfaces the terms each vendor buried, and arms you with negotiation leverage points and reference-check 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。
Presents adaptive codebase challenge questions with multiple-choice and trace exercises. Use when testing contributor knowledge of the codebase.
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。
Guides project ideation via Socratic questioning to produce a validated brief. Use before specification when requirements are unclear.
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 looking for a meta-analysis topic before any protocol exists. Starts from a professor's publication profile or from a clinical question, finds gaps, assesses feasibility and returns a ranked topic list. Running the review itself is /meta-analysis.
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 someone has a business problem, strategic question, or founder challenge they need to think through clearly. Triggers on "I'm stuck on", "should I", "what's wrong with my", "diagnose", "strategy problem", "business problem", "founder problem", "help me think through". Runs structured consulting-style diagnostic lenses to produce a comprehensive analysis.
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。
Socratic method teaching skill that guides users to discover answers themselves through questioning, never giving direct answers. TRIGGER when: user's message contains 'socratic', 'Socrates', or '소크라테스'. Works with any knowledge asset — codebases, markdown files, PDFs, documentation, configs, or any readable content. Respond in the user's language.
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。
Finding validation gate - 7-Question triage adapted for FIND schema. Run before moving any FIND from Research to Completed. One NO = keep in Research. All YES = move to Completed, then run /evidence.
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 polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth boundaries, writes polished and targeted resumes, generates interviewer-style grilling questions, answer cards, evidence-upgrade plans, and optional open-source project recommendations without fabricating experience.
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。
Analyzes and improves prompts using 31 frameworks across 7 intent categories. Use when a user wants to improve, rewrite, structure, or engineer a prompt — including requests like "help me write a better prompt", "improve this prompt", "what framework should I use", "make this prompt more effective", or any prompt engineering task. Recommends the right framework based on intent (create, transform, reason, critique, recover, clarify, agentic), asks targeted questions, and delivers a structured, high-quality result.
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。
Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor. Use when the user wants to revisit, search, extract, summarize, or compare work across Agent session stores, time ranges, projects, or named conversations. Follow the user's requested output; question clustering, problem-space mapping, artifact review, drift analysis, and insights are optional lenses.
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。
Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions. Use for meeting retrospectives, employee work reviews, decision meetings, agenda and question design, direct feedback, meeting-quality diagnosis, or repeated low-value discussions. Preserve direct standards without taking over the worker's work or degrading the truth signal.
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 why neural architectures and training methods work through forward computation, geometry, gradients, optimization dynamics, historical experiments, and competing explanations. Use for deep mechanism questions about neural networks, AI models, layers, representations, or training; explain the meaning in plain language with evidence and explicit limits.
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。
Deeply research technical architecture, source code, mechanisms, SDKs, frameworks, project comparisons, and system-design options across repositories, history, official docs, issues, discussions, and high-quality community signals. Use when the user asks for deep research, source-level understanding, architecture comparison, mechanism satisfaction, or evidence for designing a system. Always map the question and obtain confirmation before beginning substantive research; skip for simple factual lookups or straightforward implementation 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。
This skill should be used when the user asks to "brainstorm a story idea", "I have an idea for a story", "what if", "develop a premise", "is this idea strong enough", "workshop my logline", "premise", "story concept", "what should I write", "short story or novel", "novella or novel", "name my book", "title ideas", or has a spark (an image, a character, a setting, a question) and wants to turn it into a tested premise before starting a story project. NOT for the controlling idea or theme of an existing story (use theme-craft).
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。
Pre-contract vendor privacy due diligence per GDPR Article 28(1). Covers risk questionnaires, technical controls assessment, certification review, data flow analysis, and documented sufficiency decisions for processor engagement.
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。
Guides the Privacy Threshold Analysis screening process to determine whether a full DPIA is required. Provides a quick-screen questionnaire, threshold criteria based on WP248rev.01, escalation triggers, and documentation requirements. Activate when evaluating new processing activities, system changes, or procurement decisions. Keywords: PTA, privacy threshold analysis, DPIA screening, quick-screen, threshold criteria, WP248, escalation triggers.
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。
Guides APEC Cross-Border Privacy Rules system certification process including self-assessment against the APEC Privacy Framework principles, accountability agent selection, intake questionnaire completion, certification decision, annual recertification, and Global CBPR Forum transition. Keywords: APEC, CBPR, cross-border privacy, accountability agent, certification, Global CBPR.
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 uncertain questions with an explicit, user-approved web search or ChatGPT consultation, then present options and wait for implementation 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。