octagonai/skills

revenue-product-segmentation

Retrieve detailed revenue breakdown by product segment for public companies. Use when analyzing product mix, revenue concentration, segment contribution, or business line performance.

First seen Feb 2, 2026

Installation

$ npx skills add octagonai/skills --skill revenue-product-segmentation

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 125
License LICENSE
Default branch main
Open issues 1
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents windsurf

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,393 B
  • docs README.md 1,910 B
  • docs SUMMARY.md 1,789 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 251 installs

SKILL.md

Revenue Product Segmentation

Retrieve detailed revenue breakdown by product segment for public companies using Octagon MCP.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See [references/mcp-setup.md](references/mcp-setup.md) for installation instructions.

Query Format

Retrieve detailed revenue by product segment for <TICKER>, for the annual period with a flat response structure.

MCP Call:

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve detailed revenue by product segment for AAPL, for the annual period with a flat response structure"
  }
}

Output Format

The agent returns a table with revenue by product segment:

Product Segment Revenue (USD Billion)
iPhone $209.59
Services $109.16
Wearables, Home and Accessories $35.69
Mac $33.71
iPad $28.02
Total $416.17

Data Source: octagon-financials-agent

Key Insights Pattern

After receiving data, generate insights:

  1. Revenue concentration: Calculate each segment as % of total
  2. Core business identification: Identify largest revenue driver
  3. Growth segments: Note high-growth or emerging segments
  4. Diversification assessment: Evaluate revenue balance across segments
  5. Strategic positioning: Understand product portfolio mix

Analysis Tips

Revenue Concentration

Calculate segment share:

Segment Share = Segment Revenue / Total Revenue × 100

Example: $209.59B / $416.17B = 50.36%

Concentration Risk

  • Single segment >50% = high concentration
  • Top 2 segments >80% = moderate concentration
  • No segment >30% = well diversified

Segment Dynamics

Compare to prior periods:

  • Which segments are growing share?
  • Which are declining?
  • Any new segments emerging?

Margin Implications

Different segments often have different margins:

  • Services typically higher margin than hardware
  • Premium products vs commodity segments
  • Recurring vs one-time revenue

Strategic Questions

Based on segmentation:

  • Is the company transitioning its business model?
  • Are growth investments in high-margin segments?
  • How does mix compare to competitors?

Segment Analysis Framework

Hardware vs Services

For tech companies:

  • Hardware: One-time, capital intensive
  • Services: Recurring, higher margin, scalable

Geographic Implications

Segments may have geographic skew:

  • Some products stronger in certain regions
  • Currency exposure by segment
  • Regulatory considerations

Lifecycle Positioning

Segment maturity assessment:

  • Growth phase: High growth, lower margins
  • Mature: Stable, optimized margins
  • Decline: Shrinking, harvesting

Follow-up Queries

Based on results, suggest deeper analysis:

  • "What are the year-over-year growth rates for each product segment?"
  • "How do these revenue figures compare to [COMPANY]'s guidance?"
  • "What are the regional breakdowns for [SEGMENT1] and [SEGMENT2] revenue?"
  • "Compare [COMPANY]'s product segment mix to [PEER1] and [PEER2]"