prathamchopra001/skills/executive_summary
skills/executive_summary/SKILL.md
# SKILL.md ## Task Description Create a concise, structured summary of complex technical or research content, emphasizing key objectives, findings, and implications for stakeholders. ## Output Format **JSON Schema**: ```json { "objective": "Briefly state the research/analysis goal", "key_findings": ["Concise bullet points highlighting major results"], "recommendations": ["Actionable insights for decision-makers"], "uncertainties": ["Notes on limitations or data gaps"] } ``` ## D
development
Updated Apr 11, 2026
$ install --global
skillsauthnpx skillsauth add prathamchopra001/inquiro skills/executive_summaryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
SKILL.md
Task Description
Create a concise, structured summary of complex technical or research content, emphasizing key objectives, findings, and implications for stakeholders.
Output Format
JSON Schema:
{
"objective": "Briefly state the research/analysis goal",
"key_findings": ["Concise bullet points highlighting major results"],
"recommendations": ["Actionable insights for decision-makers"],
"uncertainties": ["Notes on limitations or data gaps"]
}
Decision Framework
- Prioritize: Focus on 3-5 core objectives over granular details.
- Confidence Scoring:
- High (✅): Supported by explicit data or quotes
- Medium (⚠️): Inferred from patterns, note limitations
- Low (❌): Avoid unless explicitly stated in source
- Edge Cases:
- Ambiguous data → Use "uncertainties" field
- Conflicting findings → Present both with confidence scores
Common Patterns
Example 1:
Input: "Research on renewable energy adoption in rural areas"
Output:
{
"objective": "Assess barriers to renewable energy adoption in rural regions",
"key_findings": ["High upfront costs deter 68% of rural communities", "Government subsidies increase adoption by 40%", "Lack of technical expertise persists in 72% of cases"],
"recommendations": ["Target subsidies toward low-income households", "Launch community training programs"],
"uncertainties": ["Long-term cost-benefit data insufficient"]
}
Example 2:
Input: "Analysis of AI ethics frameworks across 15 countries"
Output:
{
"objective": "Compare AI ethics regulations globally",
"key_findings": ["EU leads with comprehensive data protection laws", "Asia-Pacific nations prioritize transparency", "Sub-Saharan Africa lacks standardized frameworks"],
"recommendations": ["Promote cross-regional collaboration", "Develop adaptable compliance tools"],
"uncertainties": ["Implementation gaps in emerging markets"]
}
Anti-Patterns
- Omitting "uncertainties" when data gaps exist
- Using vague recommendations like "further research is needed"
- Exceeding 5 key findings without justification
- Including implementation details instead of high-level insights
Quality Checklist
- Verify JSON structure matches schema exactly
- Ensure all key findings are actionable and data-backed
- Confirm uncertainties are explicitly labeled and relevant
- Validate recommendations align with objectives
- Check for markdown formatting or syntax errors
- Confirm length: < 300 words total
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