SEC Filing & Earnings Analysis

I'm uploading the 10-K filing for ${company} (fiscal year ${year}). Extract and organize:

1. **INCOME STATEMENT** (3-year comparison)
| Line Item | FY${year} | FY${parseInt(year)-1} | FY${parseInt(year)-2} | YoY Change |
Revenue, COGS, Gross Profit, R&D, S&M, G&A, Operating Income, Net Income, EPS

2. **BALANCE SHEET**
| Line Item | FY${year} | FY${parseInt(year)-1} |
Cash & equivalents, AR, Total current assets, PP&E, Goodwill, Total assets, Current liabilities, Long-term debt, Total stockholders' equity

3. **CASH FLOW STATEMENT**
| Line Item | FY${year} | FY${parseInt(year)-1} |
Operating cash flow, Capex, Free cash flow, Stock-based comp, Share repurchases, Dividends

4. **KEY METRICS** (calculated from the above)
- Revenue growth rate
- Gross margin %
- Operating margin %
- Net margin %
- FCF margin %
- SBC as % of revenue
- Net cash position (cash minus debt)
- Days sales outstanding

Format all numbers in millions with one decimal place. Include the source page/note reference for each major figure.

I'm uploading the Q${quarter} earnings call transcript for ${company}. Analyze it and produce:

1. **KEY METRICS MENTIONED**
Table of every specific number the CEO/CFO cited:
| Metric | Value | Context | Comparison (if given) |

2. **GUIDANCE CHANGES**
Compare any forward guidance to what was previously guided:
| Metric | New Guidance | Prior Guidance | Change | Management Explanation |

3. **STRATEGIC SIGNALS**
Bullet list of strategic shifts, new initiatives, or changes in tone:
- What's being emphasized more than last quarter?
- What's being de-emphasized or not mentioned?
- Any new product launches, partnerships, or market entries?

4. **COMPETITIVE MENTIONS**
Every mention of competitors, market positioning, or win/loss commentary. Direct quotes with context.

5. **ANALYST CONCERNS**
What did analysts push back on or ask multiple follow-ups about? This reveals what the market is worried about.

6. **ONE-PARAGRAPH SUMMARY**
Write the summary an analyst would send to their PM after the call. "Here's what you need to know about ${company}'s Q${quarter}: ..."

Be specific. Use exact quotes from the transcript when they're revealing.

I'm uploading earnings data (transcripts, press releases, or financials) for ${company} covering the last ${quarters} quarters. Build a KPI tracking table:

| KPI | Q${startQ} | Q${startQ+1} | Q${startQ+2} | Q${startQ+3} | Trend | Flag |

KPIs to track:
- Revenue and YoY growth
- Gross margin %
- Operating margin %
- Free cash flow and FCF margin
- Customer count (total and enterprise)
- Net revenue retention / dollar-based net expansion rate
- Remaining performance obligations (RPO)
- DBNERate or NRR
- Headcount
- Revenue per employee

TREND column: Arrow and direction (↑ improving, → stable, ↓ declining)
FLAG column: 🔴 if metric degraded for 2+ consecutive quarters

Then write a 2-paragraph analysis:
1. What's improving and why
2. What's deteriorating and why

If the company changed how they report a metric (redefined, stopped disclosing), note that.

I'm uploading ${company}'s Q${quarter} earnings press release. Compare against:
- Consensus estimates: Revenue $${consensusRev}M, EPS $${consensusEPS}
- Prior quarter guidance: Revenue $${guidanceLow}M-$${guidanceHigh}M

Produce a rapid recap:

**BEAT / MISS / IN-LINE**
| Metric | Actual | Consensus | Beat/Miss | Magnitude |

**GUIDANCE RAISED / LOWERED / MAINTAINED**
| Metric | New Range | Prior Range | Direction |

**SURPRISE ITEMS**
Anything in the press release that wasn't in consensus expectations — restructuring charges, acquisition announcements, accounting changes, one-time items.

**BOTTOM LINE** (2 sentences)
What the stock reaction should be based purely on the numbers. "Beat on revenue and raised guidance — this is unambiguously positive" or "Beat on revenue but guided below consensus — the market will focus on the guide-down."

Don't editorialize. Stick to what the numbers say.

Build a public company comp table for these companies: ${companies}

I'll upload their most recent 10-K or 10-Q filings (or you can work from the data I paste in).

TABLE FORMAT:
| Metric | ${companies.split(',').join(' | ')} |

METRICS:
- LTM Revenue ($M)
- Revenue Growth (YoY %)
- Gross Margin %
- Operating Margin %
- FCF Margin %
- Net Revenue Retention (if disclosed)
- Total Customers
- Enterprise Customers (if disclosed)
- Revenue per Employee ($K)
- SBC as % of Revenue
- EV/Revenue (current)
- EV/GP (current)
- Rule of 40 score (growth + FCF margin)

Sort by Rule of 40 score, highest to lowest.

Below the table, write a 3-sentence comparative summary: who's winning on growth, who's winning on profitability, and who has the best balance.

Build a Python script that:

1. Uses the SEC EDGAR API to pull the most recent 10-Q or 10-K for a given company ticker
2. Extracts key financial data from the XBRL tags (Revenue, NetIncome, OperatingIncome, CashAndCashEquivalents, etc.)
3. Stores the extracted data in a JSON file organized by company and quarter
4. Generates a clean comparison table as an HTML file

INPUT: A list of tickers: ${tickers}
OUTPUT:
- JSON data file with extracted financials
- HTML comp table with all companies side by side
- Changelog: what metrics changed most QoQ for each company

Use the SEC EDGAR full-text search API (efts.sec.gov) and the XBRL companyfacts API.
Include proper rate limiting (SEC requires 10 requests/second max).
Include a User-Agent header with a contact email as required by SEC.

I'm uploading ${company}'s 10-K. Find the segment disclosures and produce:

1. **SEGMENT REVENUE TABLE** (3-year trend)
| Segment | FY${year} | FY${parseInt(year)-1} | FY${parseInt(year)-2} | Growth | Mix % |

2. **GEOGRAPHIC BREAKDOWN** (if disclosed)
| Region | Revenue | % of Total | Growth |

3. **ANALYSIS**
- Which segment is growing fastest?
- Is revenue concentration increasing or diversifying?
- Are there geographic regions showing deceleration?
- What does the segment margin data reveal about the business quality?

4. **RISKS**
- Customer concentration (any customer >10% of revenue?)
- Geographic concentration
- Segment-level margin compression

This is the analysis an investor would do to understand the quality and sustainability of the top-line number.