supply-chain

Generate an interactive supply chain dashboard for the company specified by the user: $ARGUMENTS

Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.

This skill maps the upstream (supplier) and downstream (customer) relationships for a target company, quantifying financial interdependencies in both directions. The output enables an analyst to understand: Who are the critical suppliers and customers? Where is concentration risk on both sides? Which suppliers depend heavily on this company for revenue? Which customers depend on this company's products as critical inputs? How does a shock propagate both upstream (demand shock to suppliers) and downstream (supply disruption to customers)?

Output Format

The final deliverable is a single self-contained HTML file with:

• Embedded CSS and JavaScript (no external dependencies)
• Tier-grouped Canvas network visualization — columns: Tier 3 → Tier 2 → Tier 1 → Target → Customers, with connection lines. Clickable nodes open detail overlays.
• Inventory Health Overview table — for all suppliers: RM%, WIP%, FG% of total inventory shown as stacked colored bars, plus latest total inventory value
• Supplier cards grouped by tier — Tier 1 (Critical/Sole-source), Tier 2 (Major Component), Tier 3 (Specialty) with click-to-expand detail overlays
• Detail overlays for each supplier containing:
  • 10-quarter financial table (Revenue, Gross Profit, Net Income, Gross Margin %)
  • 10-quarter inventory breakdown table (Raw Materials, WIP, Finished Goods, Total, RM%, WIP%, FG%)
  • Canvas chart: stacked bar chart of inventory composition with Gross Margin % line overlay
  • Business description and relationship to target company
• Customer cards grouped by category — Channel Partners, Enterprise/B2B, End-Market Exposure — with click-to-expand detail overlays matching supplier depth
• Detail overlays for each customer containing:
  • 10-quarter financial table (Revenue, Gross Profit, Net Income, Gross Margin %)
  • 10-quarter inventory breakdown table (Raw Materials, WIP, Finished Goods, Total, RM%, WIP%, FG%)
  • Canvas chart: stacked bar chart of inventory composition with Gross Margin % line overlay
  • Business description and relationship to target company
• Upstream Shock Analysis section — narrative analysis of how a demand/supply shock to the target company ripples upstream through the supplier chain, with an impact matrix table (Revenue Impact, Margin Impact, Overall Risk per supplier)
• Downstream Shock Analysis section — narrative analysis of how a supply disruption at the target company ripples downstream through the customer chain, with an impact matrix table (Input Criticality, Switching Cost, Revenue at Risk, Overall Disruption Risk per customer)
• All financial figures hyperlinked to Daloopa source citations
• A "Download as PDF" button (uses window.print())

DOM Safety: All JavaScript MUST use createElement() + textContent + appendChild() for DOM construction. NEVER use innerHTML, outerHTML, or any HTML-string injection methods. Use helper functions like ce(tag), ca(el, attrs), cA(parent, children) to keep code compact.

Save to reports/{TICKER}_supply-chain.html and open it with open.

---

RESEARCH WORKFLOW

This is a multi-phase research process. Each phase builds on the previous one. Maximize parallelism across independent API calls.

Phase 1: Target Company Identification

1. Use discover_companies with the ticker symbol to get the company_id, latest_calendar_quarter, and latest_fiscal_quarter. Note the firm name for report attribution (default: "Daloopa") — see ../data-access.md Section 4.5.
2. Pull key financials for the target company:
   • Use discover_company_series with keywords: ["revenue", "cost of goods", "gross profit", "operating income", "net income", "total cost"]
   • Calculate 4 quarters backward from latest_calendar_quarter. Use get_company_fundamentals for those periods to get TTM figures.
3. Note the target company's total COGS / cost of revenue (TTM) — this is the denominator for supplier % calculations.

Phase 2: Supplier Identification

Run these concurrently to build a comprehensive supplier list:

2a. Daloopa Document Search:

• Search keywords: ["supplier", "vendor", "purchase", "procurement"] across last 2-4 quarters
• Search keywords: ["supply agreement", "supply chain", "manufacturing"] across last 2-4 quarters
• Search keywords: ["sole source", "single source", "key supplier"] across last 2-4 quarters
• Search keywords: ["concentration", "significant supplier"] across last 2-4 quarters
• Search the company's 10-K specifically for supplier disclosures

2b. Web Research:

• "[TICKER] [company name] key suppliers list 2025 2026" — supplier identification
• "[TICKER] supply chain analysis suppliers" — analyst/industry reports
• "[TICKER] 10-K supplier disclosure" — SEC filing analysis
• "[company name] supply chain map" — industry supply chain maps
• "[company name] supplier concentration risk" — risk analysis
• "[company name] who manufactures for [company]" — manufacturing partners
• "[company name] component suppliers" — component-level supply chain

2c. Industry-Specific Supplier Research: For each industry, search for the known critical supply chain relationships:

• Tech/Hardware: semiconductor foundries (TSMC, Samsung), display (Samsung, LG, BOE), memory (Samsung, SK Hynix, Micron), sensors/cameras (Sony), glass (Corning), connectors (Amphenol), batteries (CATL, LG Energy), PCB/assembly (Foxconn/Hon Hai, Pegatron, Luxshare)
• Automotive: battery (CATL, Panasonic, LG Energy), semiconductors (Infineon, NXP, ON Semi, TI), steel (Nippon, POSCO), tires (Michelin, Bridgestone), glass (AGC, Saint-Gobain)
• Pharma: CDMOs (Lonza, Samsung Biologics, Catalent), API suppliers, packaging, distribution
• Retail: brand suppliers, logistics (FedEx, UPS), packaging
• Energy: equipment (Baker Hughes, Schlumberger), pipe (Tenaris), chemicals

Phase 3: Supplier Financial Analysis

For each identified supplier (aim for 8-15 key suppliers):

1. Discover the supplier using discover_companies with their ticker
2. Pull key financials from Daloopa:
   • discover_company_series with keywords: ["revenue", "net income", "gross margin", "operating margin"]
   • get_company_fundamentals for the same 4 calendar quarters as the target company
3. Determine revenue concentration:
   • Search Daloopa documents for the supplier: keywords ["[target company name]", "customer", "concentration"]
   • Web search: "[supplier name] [target company] revenue percentage customer"
   • Web search: "[supplier name] 10-K customer concentration"
   • Many suppliers disclose their top customers in 10-K filings — look for "customers that accounted for 10% or more of revenue"
   • Source quality (MANDATORY): these are factual claims — accept them only from primary sources (SEC filings, IR pages, press releases, transcripts) or Tier-1 financial press (Reuters, Bloomberg, WSJ, FT) per ../data-access.md Section 2.5. Never source concentration figures from Yahoo Finance editorial, Benzinga, Seeking Alpha, Motley Fool, Zacks, TipRanks, StockTwits, Reddit, or similar aggregators/blogs; if a figure only appears there, corroborate it or flag it as unverified.
4. Determine COGS attribution (what % of target's costs is this supplier):
   • This is often estimated. Use logic like:
     • If Apple's COGS is ~$200B TTM and TSMC's revenue from Apple is ~$70B, then TSMC = ~35% of COGS
     • Cite the source of each estimate (analyst report, 10-K disclosure, industry research)
   • Flag when this is an estimate vs. a disclosed figure
5. Business & product description: What does this supplier provide? Be specific (e.g., "5nm/3nm chip fabrication for A-series and M-series SoCs" not just "semiconductors")

Phase 3b: Inventory & 10-Quarter Financial Data

For the target company AND each identified supplier (8-15 companies), pull 10 quarters of data:

1. Discover inventory series using discover_company_series with keywords: ["raw material", "work in process", "finished good", "inventory", "inventories"]
   • Look for separate RM, WIP, FG series, plus a total inventory series
   • Some companies report "carrying amount" breakdowns — use those for RM/WIP/FG splits
2. Discover financial series using discover_company_series with keywords: ["revenue", "gross profit", "net income", "gross margin"]
3. Pull 10 quarters using get_company_fundamentals. Calculate 10 quarters backward from latest_calendar_quarter.
   • Example: if latest is Q4'25, pull ["2023Q3", "2023Q4", "2024Q1", "2024Q2", "2024Q3", "2024Q4", "2025Q1", "2025Q2", "2025Q3", "2025Q4"]
4. Compute inventory composition: For each quarter, calculate RM%, WIP%, FG% of total inventory
   • High WIP% can signal production bottlenecks
   • Rising FG% can signal demand weakness
   • Rising RM% can signal supply hoarding or procurement buildup
5. Handle missing data gracefully: Some suppliers may not report full inventory breakdowns — show what's available and note gaps
6. Multi-currency handling: Note the reporting currency for each company (USD, NTD, KRW, EUR, etc.) and display with appropriate units (e.g., "NTD B" for TSMC, "KRW T" for Samsung)

Run inventory and financial series pulls in parallel across all companies.

Phase 4: Customer / Downstream Identification

The downstream side requires the same research rigor as the upstream side. Run these concurrently to build a comprehensive customer list:

4a. Daloopa Document Search (target company filings):

• Search keywords: ["customer", "contract", "agreement", "channel"] across last 2-4 quarters
• Search keywords: ["customer concentration", "significant customer", "major customer"] across last 2-4 quarters — many companies disclose customers >10% of revenue
• Search keywords: ["distribution", "retail partner", "reseller", "licensee"] across last 2-4 quarters
• Search keywords: ["accounts receivable", "contract asset", "deferred revenue"] — concentration in A/R often reveals customer dependency even when not explicitly named
• Search the company's 10-K specifically for customer disclosures and segment end-market breakdowns

4b. Web Research:

• "[TICKER] [company name] major customers list" — direct customer identification
• "[TICKER] customer concentration revenue breakdown" — analyst/industry reports
• "[TICKER] 10-K customer disclosure" — SEC filing analysis
• "[company name] who buys from [company name]" — downstream identification
• "[company name] channel partners distributors" — channel analysis
• "[company name] end market exposure" — end-market breakdown

4c. Industry-Specific Customer Research: For each industry, search for the known critical downstream relationships:

• Semiconductors: Which OEMs depend on these chips? (e.g., NVDA → hyperscalers MSFT/AMZN/GOOG, QCOM → smartphone OEMs AAPL/Samsung, AVGO → networking OEMs Cisco/Arista)
• Components/Materials: Which assemblers or product companies use these inputs? (e.g., Corning → AAPL/Samsung for glass, TSMC → fabless semis NVDA/AMD/AAPL)
• Software/Platform: Who builds on this platform? (e.g., MSFT Azure → ISVs, AAPL App Store → developers, Salesforce → SI partners)
• Consumer products: Channel partners (carriers, retailers, e-commerce) and enterprise customers
• Industrial/B2B: End-market verticals (auto, aerospace, medical, telecom)
• Pharma/Biotech: Distributors (McKesson, AmerisourceBergen), PBMs, hospital systems

4d. Customer Financial Analysis:

For each identified customer (aim for 6-10 key customers):

1. Discover the customer using discover_companies with their ticker
2. Pull key financials from Daloopa:
   • discover_company_series with keywords: ["revenue", "net income", "gross margin", "cost of goods", "operating income"]
   • get_company_fundamentals for the same 4 calendar quarters as the target company
3. Determine revenue attribution (what % of target's revenue comes from this customer):
   • Search Daloopa documents for the target company: keywords ["[customer name]", "customer", "concentration", "accounts receivable"]
   • Web search: "[target company] [customer name] revenue percentage"
   • Web search: "[target company] 10-K customer concentration"
   • Many companies disclose customers that account for >10% of revenue in their 10-K
   • Source quality (MANDATORY): same rule as the supplier analysis — attribution figures only from primary sources or Tier-1 financial press per ../data-access.md Section 2.5; never from Yahoo Finance editorial, Benzinga, Seeking Alpha, Motley Fool, Zacks, TipRanks, StockTwits, Reddit, or similar aggregators/blogs. Corroborate or flag as unverified.
4. Determine input criticality (what % of customer's COGS comes from target):
   • This is the inverse of the supplier analysis: if the target sells $X to a customer with $Y in COGS, then input share = X/Y
   • Search for: "[customer name] [target company] supplier dependence" or "[customer name] key inputs components"
   • Flag whether the target's product is a critical, hard-to-substitute input vs. a commodity with alternatives
5. Assess switching costs: Can the customer easily replace the target company's product?
   • High switching cost: Custom/proprietary integration, long qualification cycles, regulatory requirements (e.g., TSMC's process node — customers can't easily switch foundries mid-design)
   • Medium switching cost: Some integration required but alternatives exist with 6-12 month transition
   • Low switching cost: Commodity input, multiple qualified alternatives, short switching timeline
6. Business & product description: What does the target supply to this customer? Be specific (e.g., "A17 Pro and M4 SoCs fabricated on TSMC's 3nm process" not just "chips")

Phase 4e: Customer Inventory & 10-Quarter Financial Data

Mirror Phase 3b for the customer side. For each identified customer (6-10 companies), pull 10 quarters of data:

1. Discover inventory series using discover_company_series with keywords: ["raw material", "work in process", "finished good", "inventory", "inventories"]
   • Look for separate RM, WIP, FG series, plus a total inventory series
2. Discover financial series using discover_company_series with keywords: ["revenue", "gross profit", "net income", "gross margin"]
3. Pull 10 quarters using get_company_fundamentals with the same 10 calendar quarters as the target company and suppliers (calculated from latest_calendar_quarter)
4. Compute inventory composition: RM%, WIP%, FG% of total inventory
   • For customers, inventory signals have different meaning:
   • Rising RM% at a customer → they're stocking up on target company's inputs (bullish for target's near-term revenue, but may mean future destocking)
   • Falling RM% → customer is drawing down inventory, may signal reduced orders ahead
   • Rising FG% at a customer → demand for the customer's end product is softening, which will flow back upstream to the target
5. Handle missing data gracefully: Some customers may not report inventory breakdowns — show what's available
6. Multi-currency handling: Same as suppliers — note reporting currency

Run customer inventory and financial series pulls in parallel, and in parallel with supplier pulls where possible.

Phase 5: Tier 2 Supplier Research

For the top 3-5 most important Tier 1 suppliers, repeat a lighter version of Phase 2-3:

1. Identify their key suppliers (Tier 2 to the original target)
2. Pull basic financials
3. Determine what they supply and rough revenue/cost relationships
4. This enables the "drill deeper" functionality in the dashboard

Phase 6: Data Assembly & Synthesis

Before writing HTML, organize all data into this structure:

TARGET COMPANY:
  - Name, ticker, description
  - TTM Revenue, COGS, Gross Profit, Net Income, Gross Margin, Op Margin
  - Market cap, stock price (from web)

TIER 1 SUPPLIERS (sorted by estimated % of target COGS, descending):
  For each:
  - Name, ticker, description
  - What they supply (specific products/components)
  - Estimated % of target company COGS (with source/logic)
  - % of supplier revenue from target company (with source)
  - TTM Revenue, Net Income, Gross Margin
  - Market cap
  - Relationship summary (sole source? multi-source? critical?)
  - Their key suppliers (Tier 2) if researched
  - 10-quarter financials: Revenue, Gross Profit, Net Income, GM% (with Daloopa citation IDs)
  - 10-quarter inventory: RM, WIP, FG, Total, RM%, WIP%, FG% (with Daloopa citation IDs)
  - Reporting currency and unit (e.g., USD $M, NTD B, KRW T)

TIER 1 CUSTOMERS (sorted by estimated % of target revenue, descending):
  For each:
  - Name, ticker, description
  - What target company supplies to them (specific products/services)
  - Estimated % of target revenue from this customer (with source/logic)
  - Estimated % of customer COGS from target (input criticality, with source)
  - Switching cost assessment (High/Medium/Low with reasoning)
  - TTM Revenue, COGS, Net Income, Gross Margin
  - Market cap
  - Relationship summary (exclusive? multi-source? long-term contract? spot?)
  - 10-quarter financials: Revenue, Gross Profit, Net Income, GM% (with Daloopa citation IDs)
  - 10-quarter inventory: RM, WIP, FG, Total, RM%, WIP%, FG% (with Daloopa citation IDs)
  - Reporting currency and unit (e.g., USD $M, EUR M, JPY B)

TIER 2 CUSTOMERS (for top 3-5 Tier 1 customers — who do THEY sell to?):
  For each Tier 1 customer, their key customers with basic data
  This traces the value chain forward: Target → Customer → End Market

TIER 2 SUPPLIERS (for top 3-5 Tier 1 suppliers):
  For each Tier 1 supplier, their key suppliers with basic data

Phase 6b: Upstream Shock Analysis (Demand Shock → Suppliers)

Prepare a narrative analysis of how a demand shock at the target company would ripple upstream through the supplier chain:

1. Classify each supplier by dependency level:

   • High dependency: Target company is >20% of supplier's revenue → severe impact from demand shock
   • Moderate dependency: Target is 10-20% of revenue → meaningful but manageable impact
   • Low dependency: Target is <10% of revenue → diversified, minimal direct impact

2. Assess shock propagation for each supplier:

   • Revenue Impact (High/Medium/Low): Based on % of revenue from target
   • Margin Impact (High/Medium/Low): Based on operating leverage, fixed costs, ability to find replacement demand
   • Inventory Risk: Suppliers with high FG% are more exposed to demand shocks; those with high RM% face supply-side risk
   • Substitutability: Can the target switch to alternatives? Can the supplier find other customers?

3. Build an impact matrix table with columns: Supplier, Tier, Revenue Dependency, Revenue Impact, Margin Impact, Overall Risk

4. Write narrative sections:

   • "Most Exposed Suppliers" — 2-3 paragraphs on suppliers facing highest risk
   • "Resilient Suppliers" — suppliers with diversified revenue bases
   • "Second-Order Effects" — how Tier 2 suppliers would be indirectly affected
   • "Key Monitoring Metrics" — what an analyst should watch (inventory days, order backlog, etc.)

Phase 6c: Downstream Shock Analysis (Supply Disruption → Customers)

Prepare a narrative analysis of how a supply disruption at the target company (production halt, quality issue, capacity constraint, export ban) would ripple downstream through the customer chain:

1. Classify each customer by input criticality:

   • Critical input: Target's product is a key component with no drop-in replacement; disruption halts customer production (e.g., TSMC to Apple — no alternative foundry for A-series chips)
   • Important input: Target is a significant but not sole supplier; customer can partially substitute with 3-6 month lead time
   • Supplementary input: Target provides a non-critical input; customer has multiple qualified alternatives

2. Assess downstream disruption for each customer:

   • Input Criticality (High/Medium/Low): How essential is the target's product to the customer's operations?
   • Switching Cost (High/Medium/Low): How long and expensive to qualify an alternative? Are there contractual lock-ins?
   • Revenue at Risk: What portion of the customer's revenue depends on products that use the target's inputs?
   • Inventory Buffer: Does the customer hold significant RM inventory of the target's product? How many weeks/months of supply?
   • Alternative Sources: Who else could supply this? What's the capacity gap?

3. Build a downstream impact matrix table with columns: Customer, Category, Input Criticality, Switching Cost, Revenue at Risk, Inventory Buffer, Overall Disruption Risk

4. Write narrative sections:

   • "Most Vulnerable Customers" — customers who would face production disruption or revenue loss
   • "Customers with Alternatives" — those who can substitute away from the target
   • "Pricing Power Implications" — if the target faces a supply constraint, which customers have the leverage to secure allocation vs. which get cut first?
   • "Channel Inventory Signals" — what customer inventory levels (especially RM%) tell you about near-term order patterns for the target company
   • "Second-Order Downstream Effects" — how end consumers or Tier 2 customers would be affected

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HTML TEMPLATE & DESIGN SYSTEM

Start from the HTML Report Template in ../design-system.md (copy the full <style> block). Then add the following additional CSS for interactive dashboard components. Use the design system's color palette throughout.

Design Principles

• Follow ../design-system.md for color palette, typography, and table conventions
• Information density: Show data compactly but with clear hierarchy
• Interactive but not flashy: Smooth transitions, click-to-expand, no animations for animation's sake

Core CSS

Start with the full CSS from ../design-system.md, then append these dashboard-specific styles:

<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>[TICKER] Supply Chain Dashboard</title>
<style>
  /* === PASTE FULL CSS FROM design-system.md HTML Report Template HERE === */

  /* === DASHBOARD-SPECIFIC EXTENSIONS BELOW === */

  @media print {
    .no-print { display: none !important; }
    .interactive { pointer-events: none; }
    @page { margin: 0.5in; size: landscape; }
  }

  :root {
    /* Extended palette for dashboard components — supplements design-system.md vars */
    --bg: var(--light-gray);
    --surface: #ffffff;
    --border: var(--mid-gray);
    --border-light: var(--light-gray);
    --text-primary: var(--near-black);
    --text-secondary: var(--dark-gray);
    --text-tertiary: #8a8a85;
    --accent: var(--steel-blue);
    --green-bg: #f0f9f2;
    --red-bg: #fef2f2;
    --amber: #92600a;
    --amber-bg: #fefce8;
    --blue-bg: #eff6ff;
    --node-supplier: var(--mid-gray);
    --node-customer: #dde8f0;
    --node-target: var(--navy);
    --sans: "Segoe UI", -apple-system, BlinkMacSystemFont, Arial, sans-serif;
    --mono: "SF Mono", "Fira Code", "Fira Mono", "Roboto Mono", monospace;
  }