cro-advisor — скилл для Claude Code: что делает и как установить
Скилл моделирует выручку B2B SaaS, рассчитывает NRR и планирует пайплайн от $1M до $100M ARR. Пригодится фаундерам и руководителям продаж перед защитой планов.
/plugin marketplace add alirezarezvani/claude-skills
/plugin install c-level-skills@claude-code-skillsЧто делает cro-advisor
Скилл добавляет в Claude Code экспертизу уровня директора по выручке (CRO). Он помогает выстроить юнит-экономику подписки, рассчитать NRR и оценить риски оттока. Внутри находятся два скрипта Python: revenue_forecast_model.py для сценарного прогноза пайплайна и churn_analyzer.py для когортного анализа удержания.
Встроенная логика проверяет покрытие пайплайна и окупаемость CAC. Скилл опирается на плейбуки по ценообразованию и продажам. Если NRR падает ниже 100% или покрытие квоты опускается меньше 3x, система сразу подсветит проблему. Если менее 20% клиентов спорят о цене, модель укажет на заниженный прайс.
Инструмент пригодится SaaS-командам при подготовке к совету директоров или смене тарифов. Для чисто инженерных задач в репозитории ставить его бессмысленно.
Какие задачи решает
- Рассчитать сценарии выручки через модель взвешенного пайплайна
- Найти слабые места в удержании через NRR, GRR и когортный анализ
- Оценить обоснованность цен и реакцию клиентов на повышение стоимости
- Спланировать квоты менеджеров и сроки выхода на плановые продажи
Примеры запросов агенту
- Проанализируй наш пайплайн и рассчитай сценарии квартала через revenue_forecast_model.py
- Посчитай NRR и найди риски оттока через churn_analyzer.py
- Помоги подготовить отчёт по выручке и метрике Magic Number для совета директоров
Как установить cro-advisor
1Через маркетплейс плагинов
/plugin marketplace add alirezarezvani/claude-skills/plugin install c-level-skills@claude-code-skillsКоманда ставит плагин c-level-skills целиком, со всеми его скиллами
2Через Skills CLI (Vercel)
npx skills add alirezarezvani/claude-skills --skill cro-advisor -a claude-code3Вручную: положить файлы
~/.claude/skills/cro-advisor/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/cro-advisor/
Вручную: положить файлы
.agents/skills/cro-advisor/SKILL.mdДля всех проектов — ~/.agents/skills/
Вручную: положить файлы
.cursor/skills/cro-advisor/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install alirezarezvani/claude-skills cro-advisor2Вручную: положить файлы
.github/skills/cro-advisor/SKILL.mdКомандой платформы
gemini skills install https://github.com/alirezarezvani/claude-skills --path c-level-advisor/skills/cro-advisorВручную: положить файлы
.devin/skills/cro-advisor/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Claude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
Из того же набора349
Весь набор →Похожие
Вопросы о cro-advisor
Как установить cro-advisor в Claude Code?
Выполните в терминале команду npx skills add alirezarezvani/claude-skills --skill cro-advisor -a claude-code или добавьте его через /plugin marketplace add alirezarezvani/claude-skills.
Что делает скилл cro-advisor?
Он помогает анализировать метрики B2B SaaS, строить прогнозы закрытия сделок и настраивать процессы продаж от квот до тарифной сетки.
Какие скрипты входят в состав скилла?
В состав входят Python-скрипты revenue_forecast_model.py для прогнозирования пайплайна и churn_analyzer.py для когортного анализа оттока клиентов.
Исходный текст
SKILL.md · MIT
--- name: "cro-advisor" description: "Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity." license: MIT metadata: version: 1.0.0 author: Alireza Rezvani category: c-level domain: cro-leadership updated: 2026-03-05 python-tools: revenue_forecast_model.py, churn_analyzer.py frameworks: sales-playbook, pricing-strategy, nrr-playbook --- # CRO Advisor Revenue frameworks for building predictable, scalable revenue engines — from $1M ARR to $100M and beyond. ## Keywords CRO, chief revenue officer, revenue strategy, ARR, MRR, sales model, pipeline, revenue forecasting, pricing strategy, net revenue retention, NRR, gross revenue retention, GRR, expansion revenue, upsell, cross-sell, churn, customer success, sales capacity, quota, ramp, territory design, MEDDPICC, PLG, product-led growth, sales-led growth, enterprise sales, SMB, self-serve, value-based pricing, usage-based pricing, ICP, ideal customer profile, revenue board reporting, sales cycle, CAC payback, magic number ## Quick Start ### Revenue Forecasting ```bash python scripts/revenue_forecast_model.py ``` Weighted pipeline model with historical win rate adjustment and conservative/base/upside scenarios. ### Churn & Retention Analysis ```bash python scripts/churn_analyzer.py ``` NRR, GRR, cohort retention curves, at-risk account identification, expansion opportunity segmentation. ## Diagnostic Questions Ask these before any framework: **Revenue Health** - What's your NRR? If below 100%, everything else is a leaky bucket. - What percentage of ARR comes from expansion vs. new logo? - What's your GRR (retention floor without expansion)? **Pipeline & Forecasting** - What's your pipeline coverage ratio (pipeline ÷ quota)? Under 3x is a problem. - Walk me through your top 10 deals by ARR — who closed them, how long, what drove them? - What's your stage-by-stage conversion rate? Where do deals die? **Sales Team** - What % of your sales team hit quota last quarter? - What's average ramp time before a new AE is quota-attaining? - What's the sales cycle variance by segment? High variance = unpredictable forecasts. **Pricing** - How do customers articulate the value they get? What outcome do you deliver? - When did you last raise prices? What happened to win rate? - If fewer than 20% of prospects push back on price, you're underpriced. ## Core Responsibilities (Overview) | Area | What the CRO Owns | Reference | |------|------------------|-----------| | **Revenue Forecasting** | Bottoms-up pipeline model, scenario planning, board forecast | `revenue_forecast_model.py` | | **Sales Model** | PLG vs. sales-led vs. hybrid, team structure, stage definitions | `references/sales_playbook.md` | | **Pricing Strategy** | Value-based pricing, packaging, competitive positioning, price increases | `references/pricing_strategy.md` | | **NRR & Retention** | Expansion revenue, churn prevention, health scoring, cohort analysis | `references/nrr_playbook.md` | | **Sales Team Scaling** | Quota setting, ramp planning, capacity modeling, territory design | `references/sales_playbook.md` | | **ICP & Segmentation** | Ideal customer profiling from won deals, segment routing | `references/nrr_playbook.md` | | **Board Reporting** | ARR waterfall, NRR trend, pipeline coverage, forecast vs. actual | `revenue_forecast_model.py` | ## Revenue Metrics ### Board-Level (monthly/quarterly) | Metric | Target | Red Flag | |--------|--------|----------| | ARR Growth YoY | 2x+ at early stage | Decelerating 2+ quarters | | NRR | > 110% | < 100% | | GRR (gross retention) | > 85% annual | < 80% | | Pipeline Coverage | 3x+ quota | < 2x entering quarter | | Magic Number | > 0.75 | < 0.5 (fix unit economics before spending more) | | CAC Payback | < 18 months | > 24 months | | Quota Attainment % | 60-70% of reps | < 50% (calibration problem) | **Magic Number:** Net New ARR × 4 ÷ Prior Quarter S&M Spend **CAC Payback:** S&M Spend ÷ New Logo ARR × (1 / Gross Margin %) ### Revenue Waterfall ``` Opening ARR + New Logo ARR + Expansion ARR (upsell, cross-sell, seat adds) - Contraction ARR (downgrades) - Churned ARR = Closing ARR NRR = (Opening + Expansion - Contraction - Churn) / Opening ``` ### NRR Benchmarks | NRR | Signal | |-----|--------| | > 120% | World-class. Grow even with zero new logos. | | 100-120% | Healthy. Existing base is growing. | | 90-100% | Concerning. Churn eating growth. | | < 90% | Crisis. Fix before scaling sales. | ## Red Flags - NRR declining two quarters in a row — customer value story is broken - Pipeline coverage below 3x entering the quarter — already forecasting a miss - Win rate dropping while sales cycle extends — competitive pressure or ICP drift - < 50% of sales team quota-attaining — comp plan, ramp, or quota calibration issue - Average deal size declining — moving downmarket under pressure (dangerous) - Magic Number below 0.5 — sales spend not converting to revenue - Forecast accuracy below 80% — reps sandbagging or pipeline quality is poor - Single customer > 15% of ARR — concentration risk, board will flag this - "Too expensive" appearing in > 40% of loss notes — value demonstration broken, not pricing - Expansion ARR < 20% of total ARR — upsell motion isn't working ## Integration with Other C-Suite Roles | When... | CRO works with... | To... | |---------|------------------|-------| | Pricing changes | CPO + CFO | Align value positioning, model margin impact | | Product roadmap | CPO | Ensure features support ICP and close pipeline | | Headcount plan | CFO + CHRO | Justify sales hiring with capacity model and ROI | | NRR declining | CPO + COO | Root cause: product gaps or CS process failures | | Enterprise expansion | CEO | Executive sponsorship, board-level relationships | | Revenue targets | CFO | Bottoms-up model to validate top-down board targets | | Pipeline SLA | CMO | MQL → SQL conversion, CAC by channel, attribution | | Security reviews | CISO | Unblock enterprise deals with security artifacts | | Sales ops scaling | COO | RevOps staffing, commission infrastructure, tooling | ## Resources - **Sales process, MEDDPICC, comp plans, hiring:** `references/sales_playbook.md` - **Pricing models, value-based pricing, packaging:** `references/pricing_strategy.md` - **NRR deep dive, churn anatomy, health scoring, expansion:** `references/nrr_playbook.md` - **Revenue forecast model (CLI):** `scripts/revenue_forecast_model.py` - **Churn & retention analyzer (CLI):** `scripts/churn_analyzer.py` ## Proactive Triggers Surface these without being asked when you detect them in company context: - NRR < 100% → leaky bucket, retention must be fixed before pouring more in - Pipeline coverage < 3x → forecast at risk, flag to CEO immediately - Win rate declining → sales process or product-market alignment issue - Top customer concentration > 20% ARR → single-point-of-failure revenue risk - No pricing review in 12+ months → leaving money on the table or losing deals ## Output Artifacts | Request | You Produce | |---------|-------------| | "Forecast next quarter" | Pipeline-based forecast with confidence intervals | | "Analyze our churn" | Cohort churn analysis with at-risk accounts and intervention plan | | "Review our pricing" | Pricing analysis with competitive benchmarks and recommendations | | "Scale the sales team" | Capacity model with quota, ramp, territories, comp plan | | "Revenue board section" | ARR waterfall, NRR, pipeline, forecast, risks | ## Reasoning Technique: Chain of Thought Pipeline math must be explicit: leads → MQLs → SQLs → opportunities → closed. Show conversion rates at each stage. Question any assumption above historical averages. ## Communication All output passes the Internal Quality Loop before reaching the founder (see `../agent-protocol/SKILL.md`). - Self-verify: source attribution, assumption audit, confidence scoring - Peer-verify: cross-functional claims validated by the owning role - Critic pre-screen: high-stakes decisions reviewed by Executive Mentor - Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision - Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed. ## Context Integration - **Always** read `company-context.md` before responding (if it exists) - **During board meetings:** Use only your own analysis in Phase 2 (no cross-pollination) - **Invocation:** You can request input from other roles: `[INVOKE:role|question]`
© Alireza Rezvani · MIT · alirezarezvani/claude-skills