「scoring」の検索結果

Systematic competitor analysis covering product teardowns, 12-dimension scoring rubric, feature comparison matrices, SWOT analysis, pricing model deconstruction, UX audits, and strategic action plans with stakeholder presentation templates.

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。

Marketing leadership advisor on brand strategy, demand generation, and marketing operations. Use when building a marketing strategy, planning demand-gen campaigns, designing lead scoring models, or aligning marketing with revenue.

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。

Data leadership advisor on data strategy, governance, quality, and platform decisions. Use when defining a data strategy, scoring data maturity, auditing data governance, evaluating a data platform, or designing the data org.

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。

Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success

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。

Customer leadership advisor on CX strategy, retention and expansion, and voice-of-customer programs. Use when defining a CX strategy, scoring CX maturity, planning churn interventions, or designing a VoC program.

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 marketing content using the brand glossary and do-not-translate terms, with quality scoring. "translate this into Japanese"

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 leads into a CRM with dedup, scoring and consent checks, approval-gated. "dedupe and score this lead list"

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 cohort analysis: retention matrix and LTV by cohort. Churn scoring → churn-risk. "build a retention matrix"

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 RL reward signals using the OpenJudge framework. Covers choosing between pointwise and pairwise reward strategies based on RL algorithm, task type, and cost; aggregating multi-dimensional pointwise scores into a scalar reward; pairwise tournament reward for GRPO on subjective tasks (net win rate across group rollouts); generating preference pairs for DPO/RLAIF; and normalizing scores for training stability. Use when building reward models, scoring rollouts for GRPO/REINFORCE, generating preference data for DPO, or doing Best-of-N selection.

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 custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation 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。

Risk-based vendor assessment framework for IT service providers, technology vendors, and third-party partners under DORA, NIS2, GDPR. Provides three-phase process (Initial Screening / Detailed Assessment / Final Evaluation), six-dimension risk scoring (Financial/Operational/Compliance/Security/Reputational/Strategic) with weighted matrices, full DORA Art. 28-30 contractual checklist, NIS2 Art. 21(2) security measures enumeration, GDPR Art. 28 documentation checks, red flags per dimension, trigger-based review criteria, and document templates. Use when: (1) Evaluating new vendors or technology providers, (2) Conducting critical ICT third-party due diligence under DORA, (3) Performing supply chain security assessment under NIS2, (4) Creating vendor onboarding documentation, (5) Establishing ongoing vendor monitoring, (6) Assessing concentration risk, or (7) Generating executive vendor risk reports.

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。

NIS2 Compliance Navigator — scope classification, Art. 21 gap analysis (0-4 maturity scoring), and compliance roadmap under EU Directive 2022/2555 with deep German BSIG-neu coverage and profiles for Italy, France, Netherlands, Austria, Spain. Use when: (1) User mentions "NIS2", "NIS-2", "BSIG", "BSIG-neu", "NIS2UmsuCG", "Cyberbeveiligingswet", "Loi Résilience", "NISG", "decreto legislativo 138", (2) User asks if their organization falls under NIS2 or needs a cybersecurity compliance assessment, (3) User mentions essential/important entities, Annex I/II, BSI registration, § 30 BSIG, incident reporting, management body liability, supply chain security, (4) User wants a NIS2 gap analysis, readiness assessment, or compliance roadmap, (5) User asks about NIS2 fines, enforcement, or Nachweispflicht, (6) User asks about NIS2 in any EU Member State.

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。

Contract intelligence and contract operations workflow skill for Claude and Codex. Guides the full contract lifecycle review process from intake and playbook normalization through clause review, deviation scoring, negotiation planning, approval routing, QA, and action recommendations. Reviews legal, business, operational, compliance, privacy, security, technology, and AI-related risks across contracts and legal documents. Supports NDAs, SaaS agreements, DPAs, procurement contracts, commercial agreements, contract comparisons, redlines, approval packages, clause research, and drafting. Warning-Comprehensive reviews can consume significant Claude/OpenAI tokens, especially for large agreements, playbooks, exhibits, schedules, and multi-document reviews.

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。

Review, draft, or redline a Data Processing Agreement (DPA / Auftragsverarbeitungsvertrag / AVV) under Art. 28 GDPR, or prepare a Joint Controller Arrangement under Art. 26 GDPR. Supports bilingual output (DE/EN), both controller- and processor-side perspectives, and two review depths — quick (Art. 28(3)(a)–(h) coverage) and negotiation-grade (clause-by-clause risk scoring).

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。

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.

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 blueprint for party games including minigame resource system (define via .tres files), local multiplayer input (4-player controller management), asymmetric gameplay (1v3 balance), scene management (clean minigame loading/unloading), persistent scoring (track wins across rounds), and split-screen rendering (SubViewport per player). Use for Mario Party-style games or WarioWare collections. Trigger keywords: party_game, minigame_collection, local_multiplayer, asymmetric_gameplay, split_screen, dynamic_input_mapping.

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 blueprint for rhythm games including audio synchronization (BPM conductor, latency compensation with AudioServer.get_time_since_last_mix), note highways (scroll speed, timing windows), judgment systems (Perfect/Great/Good/Bad/Miss), scoring with combo multipliers, input processing (lane-based, hold note detection), and chart/beatmap loading. Based on DDR/osu!/Beat Saber research. Trigger keywords: rhythm_game, audio_sync, timing_judgment, note_highway, combo_system, BPM_conductor, latency_compensation.

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 blueprint for party games including minigame resource system (define via .tres files), local multiplayer input (4-player controller management), asymmetric gameplay (1v3 balance), scene management (clean minigame loading/unloading), persistent scoring (track wins across rounds), and split-screen rendering (SubViewport per player). Use for Mario Party-style games or WarioWare collections. Trigger keywords: party_game, minigame_collection, local_multiplayer, asymmetric_gameplay, split_screen, dynamic_input_mapping.

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 blueprint for rhythm games including audio synchronization (BPM conductor, latency compensation with AudioServer.get_time_since_last_mix), note highways (scroll speed, timing windows), judgment systems (Perfect/Great/Good/Bad/Miss), scoring with combo multipliers, input processing (lane-based, hold note detection), and chart/beatmap loading. Based on DDR/osu!/Beat Saber research. Trigger keywords: rhythm_game, audio_sync, timing_judgment, note_highway, combo_system, BPM_conductor, latency_compensation.

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。

Search Experience Optimization: reads Google SERPs backwards to detect page-type mismatches, derives user stories from search intent signals, and scores pages from multiple persona perspectives. Identifies why well-optimized pages fail to rank by analyzing what Google rewards for each keyword. Use when user says "SXO", "search experience", "page type mismatch", "SERP analysis", "user story", "persona scoring", "why isn't my page ranking", "intent mismatch", or "wireframe".

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 content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".

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 help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes. Also use when the user mentions 'RevOps,' 'revenue operations,' 'lead scoring,' 'lead routing,' 'MQL,' 'SQL,' 'pipeline stages,' 'deal desk,' 'CRM automation,' 'marketing-to-sales handoff,' or 'data hygiene.' For cold outreach emails, see cold-email. For email drip campaigns, see email-sequence. For pricing decisions, see pricing-strategy.

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。

Pulls replies from a Smartlead campaign, classifies each as positive/neutral/negative/OOO/bounce/unsubscribe using Claude, and reports the positive reply rate — the north-star metric for cold email. Use when the user wants to know if a campaign is actually working (not just getting replies, but getting the RIGHT replies). Triggers on "score my replies", "how's campaign X doing", "positive reply rate", "is this campaign working".

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。

Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.

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。