1,523 件 ・ 関連度順
概要と使いどころ
Leverages Ahrefs REST API v3 to identify content gap opportunities through competing domain analysis. Pulls referring domains data, anchor text distributions, and DR metrics to prioritize content creation for link-worthy topics.
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 support operations guidance for customer service excellence. Use when designing ticket management systems, creating SLA policies, building support tier structures (L1/L2/L3), optimizing knowledge bases, defining severity levels and escalation procedures, implementing support metrics (CSAT, FRT, TTR, FCR), configuring support tool stacks, or building support-to-CS feedback loops. Covers Zendesk, Intercom, Freshdesk, and help desk best 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。
Strategic Customer Success leadership guidance for CS org design, customer segmentation and tiering (tech touch, low touch, high touch), success metrics and KPIs (NRR, GRR, NPS, CSAT, CES), playbook development, executive stakeholder management, CS technology stack strategy, value realization frameworks, and customer journey mapping. Use when building CS teams, defining customer segments, designing playbooks, measuring success outcomes, or implementing CS platforms.
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 product management guidance for day-to-day PM work. Use when creating roadmaps, prioritizing features, managing stakeholders, planning sprints, grooming backlogs, scoping features, planning releases, defining OKRs, managing technical debt, or coordinating go-to-market. Covers RICE, ICE, MoSCoW frameworks, cross-functional collaboration, and product metrics.
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 product launch strategist for SaaS and technology companies. Use when planning product launches, coordinating cross-functional launch teams, managing beta programs, creating launch communication plans, planning launch day execution, setting up post-launch monitoring, running launch retrospectives, or defining launch metrics. Covers launch tiering, internal enablement, rollback planning, and contingency strategies.
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 growth product management guidance for SaaS applications. Use when designing growth loops, optimizing activation and onboarding, building retention systems, creating referral mechanics, running growth experiments, defining north star metrics, or implementing PLG strategies. Covers the full growth lifecycle from acquisition to monetization.
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 product specification and documentation writer. Use when creating PRDs, user stories, acceptance criteria, technical specifications, API documentation, edge case analysis, design handoff docs, feature flag plans, or success metrics. Covers the full spectrum from high-level requirements to implementation-ready specifications.
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 pricing strategy and monetization guidance for SaaS and digital products. Use when designing pricing tiers, creating pricing pages, setting value metrics, developing bundle strategies, planning price increases, writing pricing copy, analyzing competitive pricing, or optimizing annual vs monthly positioning. Use for packaging decisions, discount policies, enterprise pricing, and behavioral pricing tactics.
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 product analytics strategist for SaaS and digital products. Use when designing product metrics frameworks, funnel analysis, cohort retention, feature adoption tracking, A/B testing, experimentation design, data instrumentation, or product dashboards. Covers AARRR, HEART, behavioral analytics, and impact measurement.
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 Quarterly Business Review facilitation for maximizing customer value and strategic alignment. Use when designing QBR programs, preparing executive presentations, demonstrating ROI and value realization, conducting strategic account planning, aligning product roadmaps, identifying risks and opportunities, facilitating business reviews, or automating QBR processes. Use for EBR preparation, success metrics presentation, renewal preparation, and stakeholder 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。
Expert customer health scoring and analytics guidance. Use when designing health scores, building churn prediction models, analyzing usage metrics, identifying at-risk accounts, creating executive dashboards, or performing cohort analysis. Use for leading indicator development, customer data enrichment, risk escalation frameworks, and retention analytics.
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。
The Mileva Method (CRISP) — Phase 5: Prove. Success validation against Phase R baseline metrics, test log review, and AI justification validation. Use after deployment. Triggers on "prove", "phase 5", "validate", "did it work", "success criteria", "measure results", or after go-live.
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 web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge.
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 which external metric sources apply to this product (GitHub, Plausible, Stripe, etc.) and configure adapters. Retrofit entry point for projects that started before v0.14; also runnable to refresh source list when the product grows.
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 eval scenarios to benchmark Mycelium effectiveness. Execute tasks using reflexion loop, validate against success criteria, record metrics.
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 working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).
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。
Assesses marketplace dynamics with take rate analysis, liquidity metrics, supply/demand balance, and network effect strength. Use when evaluating marketplaces, analyzing take rates, or assessing network effect moats.
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。
Structures industry-level credit assessment with cyclicality analysis, regulatory risk, and sector-specific credit metrics. Use when analyzing industry credit conditions, evaluating sector risk, or building industry-level views.
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。
Deconstructs unit economics with CAC, LTV, payback period, gross margin, and contribution margin analysis. Use when analyzing unit economics, validating SaaS metrics, or assessing business model efficiency.
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。
Evaluates master and special servicer performance with delinquency management, modification outcomes, and loss mitigation effectiveness. Use when assessing servicer quality, monitoring servicing metrics, or evaluating servicer transfers.
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。
Constructs fund-level performance reporting with IRR, MOIC, DPI, RVPI, PME, and vintage year benchmarking. Use when building fund reports, calculating performance metrics, or preparing LP reporting packages.
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。
Evaluates sales efficiency with CAC payback, sales cycle analysis, channel economics, and pipeline conversion metrics. Use when assessing GTM efficiency, analyzing sales productivity, or evaluating distribution 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。
Evaluates PLG dynamics with viral coefficients, freemium conversion, product-qualified leads, and expansion revenue mechanics. Use when analyzing PLG companies, assessing virality, or evaluating product-driven acquisition.
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 startup financial models for investor readiness: validates unit economics, stress-tests runway scenarios, and benchmarks metrics against stage-appropriate targets. Use the full review, about 10–15 minutes, when the user provides a financial model (Excel, CSV, or a model pasted as text) and asks for review, validation, runway analysis, or unit-economics scoring. For a single money question with figures to compute, such as 'how long do I have?' or 'is a 4x burn multiple bad?', use its shorter quick check, so the answer comes from the calculator and dated benchmarks, not mental arithmetic.
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。