ceo-advisor

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Tool: SKILL.md [1/2] Description: --- name: ceo-advisor description: Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Includes strategy analyzer, financial scenario modeling, board governance frameworks, and investor relations playbooks.

Tool: SKILL.md [2/2] Description: Management ### Company Scorecard **Financial Metrics**: - Revenue growth - Gross margin - EBITDA - Cash flow - Runway **Customer Metrics**: - Acquisition - Retention - NPS - LTV/CAC **Operational Metrics**: - Productivity - Quality - Efficiency - Innovation **People Metrics**: - Engagement - Retention - Diversity - Development ### CEO Self-Assessment **Quarterly Reflection**: - What went well?

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Tool: references/board_governance_investor_relations.md [1/2] Description: # Board Governance & Investor Relations Guide ## Board of Directors Management ### Board Composition #### Ideal Board Structure - **Size**: 7-9 members (odd number for voting) - **Independence**: Majority independent directors - **Diversity**: Gender, ethnicity, expertise, experience - **Term**: 3-year terms, staggered renewal #### Board Roles | Role | Responsibilities | Typical Background | |------|-----------------|----

Tool: references/board_governance_investor_relations.md [2/2] Description: Engagement Phase** - Direct dialogue - Understanding demands - Finding common ground - Negotiation strategy **3.

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Tool: references/executive_decision_framework.md [1/2] Description: # Executive Decision Framework ## Decision-Making Process ### The DECIDE Framework **D** - Define the problem clearly **E** - Establish criteria for solutions **C** - Consider alternatives **I** - Identify best alternatives **D** - Develop and implement action plan **E** - Evaluate and monitor solution ## Strategic Decision Categories ### 1. Growth Decisions #### Market Expansion **Evaluation Criteria**: - Market size and growth

Tool: references/executive_decision_framework.md [2/2] Description: Customer lifetime value #### Internal Process - Operational efficiency - Time to market - Quality metrics - Innovation rate - Process cycle time #### Learning & Growth - Employee engagement - Talent retention - Training hours per employee - Leadership pipeline - Innovation index ## Decision Biases to Avoid ### Cognitive Biases 1.

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Tool: references/leadership_organizational_culture.md [1/2] Description: # Leadership & Organizational Culture Guide ## Leadership Philosophy ### The Five Dimensions of CEO Leadership 1.

Tool: references/leadership_organizational_culture.md [2/2] Description: academy - Mentorship program - Rotation opportunities - Tuition reimbursement - Conference attendance - Skill workshops **Wellbeing Initiatives**: - Flexible work arrangements - Mental health support - Wellness programs - Time-off policies - Family support - Financial wellness ## Performance Management ### OKR Framework #### OKR Setting Process **Company OKRs** (Annual) ↓ **Department OKRs** (Quarterly) ↓ **Team OKRs** (Qua

Malicious tool definition detected

Tool: scripts/financial_scenario_analyzer.py [1/2]

Tool: scripts/financial_scenario_analyzer.py [2/2] Description: -> Dict: """Generate recommendation based on analysis""" recommendation = { 'recommended_scenario': '', 'rationale': [], 'key_actions': [], 'risk_mitigation': [] } # Find optimal scenario best_risk_adjusted = max(scenarios, key=lambda s: s['npv'] * s['probability']) recommendation['recommended_scenario'] = best_risk_adjusted['name'] # Generate rationale if best_risk_adjusted['npv'] > 0: recommendation['rationale'].append(f"Positive

Malicious tool definition detected

Tool: scripts/strategy_analyzer.py [1/2]

Tool: scripts/strategy_analyzer.py [2/2] Description: sum(factors) / len(factors) def _calculate_financial_risk(self, data: Dict) -> float: """Calculate financial risk""" financial = data.get('financial_health', {}) factors = [ 100 - financial.get('cash_flow', 50), 100 - financial.get('profitability', 50), data.get('debt_ratio', 50), data.get('burn_rate', 50) if 'burn_rate' in data else 30 ] return sum(factors) / len(factors) def _calculate_competitive_risk(self, data: Dict) -> float: """Calcula