skills/ceo-council/SKILL.md
Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots
npx skillsauth add serejaris/ris-claude-code ceo-councilInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Launch parallel sub-agents as isolated C-level experts. Each analyzes the same project data from their perspective. No coordination between experts — isolation produces genuine diversity of opinion. Then synthesize consensus and disagreements.
MUST use the Task tool with subagent_type: "general-purpose" and model: "opus".
Task(
subagent_type: "general-purpose",
model: "opus",
prompt: "<expert prompt with data>",
description: "CFO analysis"
)
DO NOT use bash, shell scripts, or background commands to launch experts. They will fail.
Launch all experts in a single message with multiple Task tool calls for true parallelism.
Before suggesting experts, understand the project:
CLAUDE.md (or README.md if absent).claude/rules/ for domain contextBased on findings, generate 4-6 expert roles tailored to THIS project. Roles must reflect the project's actual domain, challenges, and stage.
MANDATORY: Ask the user before proceeding. Do not pick roles yourself.
Use AskUserQuestion with multiSelect: true:
Don't copy these — generate fresh roles based on actual project context:
| Project Type | Typical Roles | |-------------|--------------| | SaaS | Head of Engineering, Head of Product, Head of Growth, CFO, UX Researcher | | Open Source | Community Manager, Technical Architect, DevRel, Security Advisor | | Content / Media | Content Strategist, Audience Analyst, Monetization Expert, Distribution Expert | | EdTech | CMO, CFO, CPO, COO, Growth Advisor | | E-commerce | Head of Supply Chain, Marketing Director, CTO, Customer Experience Lead | | Agency / Consulting | Sales Director, Delivery Lead, Talent Manager, CFO |
Collect project state to feed all experts. Stay focused on what's relevant:
Read:
Skip: GitHub traffic stats, stargazer counts, clone data, contributor lists — these are vanity metrics, not strategic data.
All experts must receive identical data context. Prepare the data block ONCE, then paste it into each expert prompt.
For each selected expert, create a prompt with the SAME data block:
You are the [ROLE] for [PROJECT NAME]. Analyze the data below from a [DOMAIN] perspective.
Focus on:
- [3-6 specific focus areas relevant to role and project]
Data:
[CURRENT PROJECT DATA — identical for all experts]
[Role-specific instruction: "show the math", "be the contrarian", "prioritize by effort/impact", etc.]
Respond in the same language as the data provided.
Rules:
Launch ALL selected experts in one message using multiple Task tool calls:
# In a single response, call Task for each expert:
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CFO prompt>", description: "CFO analysis")
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CPO prompt>", description: "CPO analysis")
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CTO prompt>", description: "CTO analysis")
Wait for all experts to return results before proceeding to synthesis.
Do not skip this step. The synthesis is the entire value of the council.
After all experts report, create a synthesis document:
# Council Session: [DATE]
## Council Members
[List of selected experts and their focus]
## Context
[Current metrics/state snapshot — brief]
## [Expert 1 Name]
[Key findings and recommendations]
## [Expert 2 Name]
[Key findings and recommendations]
## Consensus (all agree)
1. ...
2. ...
## Disagreements
| Expert | Position | Argument |
|--------|----------|----------|
| ... | ... | ... |
## Decisions
_To be filled after discussion._
Save to a logical location:
docs/council-[DATE].md — default| Mistake | Fix | |---------|-----| | Picking roles without asking user | ALWAYS use AskUserQuestion first | | Using bash to launch experts | ONLY use Task tool with subagent_type: "general-purpose" | | Giving experts different data | Prepare ONE data block, paste into all prompts | | Gathering vanity metrics | Focus on project docs, strategy, actual metrics | | Too many experts (6+) | 3-4 is optimal for signal-to-noise | | Skipping synthesis | The synthesis IS the value — never skip |
development
Use when operating, debugging, deploying, or monitoring a Telegram bot or Telegram-to-agent gateway. Triggers on "telegram bot down", "bot not responding", "debug bot", "check webhook", "polling vs webhook", "restart bot", "deploy bot", "bot logs", "agent gateway", "Telegram Bot API error", "send test message", "бот не отвечает", "проверь бота", "логи бота", "перезапусти бота". Covers health checks, logs, webhook/polling diagnostics, environment validation, safe restart/deploy checklists, Bot API smoke tests, forum topic delivery, privacy mode, gateway routing, and incident notes.
testing
Разбивает Epic или крупное требование на независимые User Stories с acceptance criteria в формате Given-When-Then, проверкой по INVEST и оценкой Story Points (Fibonacci или T-shirt). На выходе — Story Map с предложением по Sprint-планированию. User-invoked only — do NOT auto-trigger. Triggers on /pm-user-stories, "разбей на user stories", "разбить эпик", "story map", "AC", "acceptance criteria", "break down into user stories", "split this epic", "write user stories".
research
Сводит статус итерации, оценивает прогресс milestones, фиксирует изменения приоритетов, отслеживает зависимости и выдаёт roadmap в формате Now/Next/Later с атрибуцией задержек по 5 причинам, health score и фреймворком обрезки scope при нехватке ресурсов. User-invoked only — do NOT auto-trigger. Triggers on /pm-roadmap, "обнови roadmap", "статус спринта", "анализ задержек", "update roadmap", "sprint status", "milestone progress", "delay analysis".
development
Use when ranking a list of requirements, features, or backlog items using RICE / ICE / MoSCoW / Kano. Built-in decision tree picks the right framework based on data availability and decision context. Output is a transparent matrix, 2×2 Impact/Effort quadrant, and a Sprint allocation proposal. User-invoked only — do NOT auto-trigger. Triggers on "/pm-prioritize", "/prioritize", "приоритизация", "ранжируй бэклог", "RICE-анализ", "prioritize requirements", "RICE", "ICE", "MoSCoW", "Kano", "rank backlog".