export-results

name	export-results
description	Triggers on "export", "share", "send to Slack", "make a deck", "/export".
triggers	["/export","export this","share results","send to Slack","make a deck","email summary"]

Skill: Export Results

Purpose

Export analysis results in different formats for different audiences. Converts pipeline outputs into ready-to-share deliverables.

When to Use

• User says /export or "export this as..." or "send this to..."
• After completing an analysis or pipeline run
• When the user needs results in a specific format

Invocation

/export slides — generate/refresh Marp slide deck from latest analysis /export email — write an executive summary email (markdown) /export slack — write a concise Slack update (markdown) /export brief — write a 1-page decision brief (markdown) /export data — export analysis data tables as CSV /export all — generate all text formats + data

Instructions

Step 1: Find Source Material

Check for completed analysis outputs in order of preference:

1. <workspace>/outputs/slides_*.md — latest deck
2. <workspace>/outputs/analysis_*.md — latest narrative
3. <workspace>/working/pipeline_summary.md — pipeline summary
4. <workspace>/working/storyboard_*.md — storyboard

If no outputs exist:

• Check <workspace>/working/ for partial results
• If nothing found: "No analysis results to export. Run an analysis first or use /run-analysis."

Step 2: Generate Requested Format

Format: slides

• If deck already exists, ask: "Deck found at {path}. Regenerate or export as-is?"
• If no deck, invoke Deck Creator agent with latest narrative + charts
• Output: <workspace>/outputs/slides_{DATE}.md

Format: email

• Structure: Subject line + 3-paragraph body (context, key finding, recommendation)
• Tone: Executive-friendly, no jargon, action-oriented
• Include: 1-2 key numbers, the "so what", and a clear ask
• Output: <workspace>/outputs/email_summary_{DATE}.md

Example:

Subject: Q2 Growth Update — Key Findings

Hi [Recipient],

Over the past quarter, we analyzed user growth patterns across all segments.
Here are the key findings:

**Key Finding:** Our organic segment grew 45% YoY, but our paid acquisition
channel saw a 12% decline due to increased competition. This shift has
reduced our overall CAC efficiency by 8%.

**Our Recommendation:** Shift 30% of paid budget from top-of-funnel ads
to product recommendations. Early testing shows a 3x improvement in
conversion for this channel.

What I need from you: Approval to reallocate the paid budget. I can have
the new strategy live by end of week.

Best,
[Your name]

Format: slack

• Structure: Bold headline + 3-5 bullet points + thread-friendly
• Keep under 300 words
• Use emoji sparingly (checkmarks, arrows only)
• Include: key metric, direction, and recommended action
• Output: <workspace>/outputs/slack_update_{DATE}.md

Example:

🎯 **Q2 Growth Analysis: Organic Up, Paid Down**

Key findings:
• Organic segment: +45% YoY (our strongest channel)
• Paid acquisition: -12% YoY (due to increased CPM)
• Overall CAC efficiency: -8% (needs correction)

Recommendation: Reallocate 30% of paid budget to product recommendations.
Early tests show 3x better conversion. We can launch by EOW.

Questions? Let me know in thread.

Format: brief

• Structure: Title + Executive Summary (3 sentences) + Key Findings (numbered) + Recommendation + Next Steps + Appendix (data sources, methodology)
• 1 page target (~500 words)
• Output: <workspace>/outputs/decision_brief_{DATE}.md

Example:

# Q2 Growth Analysis: Strategic Realignment

## Executive Summary

Our organic segment is thriving (+45% YoY), but our paid acquisition channel
is struggling (-12% YoY) due to increased CPM. To maintain growth while
improving profitability, we recommend reallocating 30% of paid budget to
product recommendations, which show 3x better conversion in early testing.

## Key Findings

1. **Organic Growth is Accelerating**
   - Up 45% YoY across all segments
   - Driven by brand awareness and word-of-mouth
   - Highest margin channel

2. **Paid Acquisition is Under Pressure**
   - Down 12% YoY due to increased CPM
   - CAC increased 25% while conversion remained flat
   - Requires strategic realignment

3. **Product Recommendations Are Underutilized**
   - Early tests show 3x conversion improvement vs paid ads
   - Current spend: $50K/month
   - Potential upside: $150K/month at same CAC

## Recommendation

Reallocate 30% of paid budget ($75K/month) to product recommendations.
Expected outcome: +$150K/month incremental revenue, -20% overall CAC.

## Next Steps

1. Approve budget reallocation (this week)
2. Launch expanded product recommendations (next week)
3. Track performance weekly for 4 weeks
4. Optimize based on results

## Appendix

Data sources: Orders table, user_segments table, marketing_spend table
Methodology: Cohort analysis with 90-day lookback
Confidence: 85% (based on limited test sample)

Format: data

• Export all DataFrames from <workspace>/working/ as CSVs to <workspace>/outputs/data/
• Include a README listing each file and its contents
• Output: <workspace>/outputs/data/ directory

Format: all

• Run email + slack + brief + data sequentially
• Skip slides if already exists

Step 3: Post-Export

• List all exported files with paths
• Suggest: "Copy the email to your clipboard?" or "Want to adjust the tone?"

Rules

1. Never fabricate findings — only use data from actual analysis outputs
2. Always cite the source analysis date and dataset
3. Adapt detail level to format (email = high-level, brief = medium, data = raw)
4. Apply clear, jargon-free language for all text outputs
5. If the analysis had confidence scores, include them in brief format

Edge Cases

• Partial analysis: Export what's available, note gaps: "Note: validation step was not completed."
• Multiple analyses in outputs/: Use the most recent by date, or ask user which one
• Charts missing: Text formats still work, note: "Charts not available for this export."
• User requests unknown format: List available formats and ask to choose

Export Quality Checklist

Before exporting, ensure:

• All numbers are cited (with source table)
• No jargon without explanation
• Recommendations are actionable (not vague)
• Tone matches audience (exec vs technical vs team)
• Time period is clear (what dates does this cover?)
• Confidence level is noted (if applicable)
• Next steps are specific (not "keep monitoring")