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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/prathamchopra001-executive-summary
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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What's inside
- Skill name
executive_summary- Description
- None
- License
- MIT
- Instructions
- 64 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- missing YAML frontmatter
- name: missing
- description: missing
Files (2)
- SKILL.md
- skill_meta.json
SKILL.md (first lines)
# 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"]
}
```
## Decision Framework
1. **Prioritize**: Focus on 3-5 core objectives over granular details.
2. **Confidence Scoring**:
- High (✅): Supported by explicit data or quotes
- Medium (⚠️): Inferred from patterns, note limitations
- Low (❌): Avoid unless explicitly stated in source
3. **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**:
```json
{
"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**:
```json
{
"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
1. Verify JSON structure matches schema exactly
2. Ensure all key findings are actionable and data-backed
3. Confirm uncertainties are explicitly labeled and relevant
4. Validate recommendations align with objectives
5. Check for markdown formatting or syntax errors
6. Confirm length: < 300 words totalFrom prathamchopra001/INQUIRO, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Mar 11, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/prathamchopra001/INQUIRO
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
executive_summary skill. Agent Mart. https://agentmart.dev/skills/prathamchopra001-executive-summary (last updated 2026-10-24)