bottleneck-hunter

name	bottleneck-hunter
category	strategy
description	Supply-chain bottleneck arbitrage. Given a super-trend (AI infra, energy transition, defense, semiconductor reshoring, space economy), decompose its physical supply chain down to Layer 2/3 choke points (optics, lasers, InP/SOI substrates, IC substrates, probe cards, specialty fiberglass...) and surface under-the-radar listed companies sitting on each bottleneck. Scores each link on 6 scarcity criteria, applies mandatory valuation gates (PS/PE/safety-margin) via the financial_rigor tool, and Munger-style reverse-validates. Outputs a ranked bottleneck opportunity board. Use when the user wants hidden beneficiaries of a structural trend rather than already-priced leaders.

Supply-Chain Bottleneck Hunter

Decompose a super-trend (user-specified, e.g. "AI infrastructure", "energy transition") into its physical supply chain and hunt for bottleneck-arbitrage opportunities.

Core Idea

Don't ask "which AI stock to buy" — ask "if this trend keeps expanding, which link runs out first?"

Traditional research chases leaders and known tracks. This skill inverts: start from the choke points of the physical supply chain and find companies nobody notices but that the whole industry must wait on when they run short.

The edge: Layer-1 bottlenecks (GPU, HBM, power) are already priced in. The real alpha is in Layer 2 and Layer 3 — optical modules, lasers, InP substrates, SOI wafers, epitaxy equipment, wafer-level test, IC substrates, specialty fiberglass.

Step 1: Super-Trend Confirmation

Trend Filter Criteria

Criterion	Requirement	How to verify
Durability	≥3-5 years of certain growth	Search industry forecasts, capex plans
Physicality	Needs real hardware/material/equipment build	Distinguish "software upgrade" from "physical expansion"
Scale	Global capex >$50B/year	Search top players' capex guidance
Acceleration	Demand growth > supply expansion	Compare demand growth vs capacity plans

Use web_search to verify. Reference super-trends: AI infrastructure, energy transition (nuclear/grid/storage), defense modernization, semiconductor reshoring, space economy.

Step 2: Physical Supply-Chain Decomposition

Don't stop at concepts — decompose to physical entities.

Layer 0 (end): final product/service
Layer 1 (core component): already closely watched  → priced in, limited alpha
Layer 2 (sub-component/material): low attention, alpha-rich
Layer 3 (upstream equipment/raw material)
Layer 4 (infrastructure): power, cooling, land, talent, certifications

AI Infrastructure Example

Layer 0: AI model training/inference services
Layer 1: GPU/accelerators, HBM, servers, data centers
Layer 2 (focus zone):
  - Network interconnect: optical modules, fiber, switch ASICs, copper cables
  - Optical comms core: lasers (EML/VCSEL/CW), modulators, photodetectors
  - Semiconductor materials: InP substrates, GaAs substrates, SOI wafers, SiC substrates
  - Advanced packaging: CoWoS interposers, HBM TSV, ABF substrate film
  - PCB/substrate: high-frequency PCB, IC substrates, specialty fiberglass
  - Test: wafer-level test (probe cards), burn-in, ATE
  - Thermal/cooling: liquid cooling, CDU, immersion fluid
  - Power connection: busbars, UPS, distribution, transformers
Layer 3: epitaxy equipment (MOCVD/MBE), lithography/etch, high-purity metals (In/Ga/Ge), specialty gases, sputtering targets, certifications (MSA/Telcordia)
Layer 4: power (nuclear/gas/transmission), cooling water, data-center land/permits

For other trends, use web_search with queries like {trend} supply chain bottleneck, {trend} shortage critical component, {trend} capacity constraint, {trend} sole source supplier.

Step 3: Bottleneck Identification — Finding "Choke Points"

For each Layer 2-3 link, evaluate 6 criteria:

#	Criterion	Question	Score
1	Supply concentration	≤3 global suppliers?	🔴 ≤2 / 🟡 3-5 / 🟢 >5
2	Expansion lead time	How long to add capacity?	🔴 >2y / 🟡 1-2y / 🟢 <1y
3	Substitutability	Can other tech/material replace it?	🔴 irreplaceable / 🟡 partial / 🟢 easy
4	Capacity utilization	Current utilization?	🔴 >90% / 🟡 70-90% / 🟢 <70%
5	Demand growth	Downstream demand growth?	🔴 >50%/yr / 🟡 20-50% / 🟢 <20%
6	Customer qualification cycle	How long for a new supplier to qualify?	🔴 >1y / 🟡 6-12m / 🟢 <6m

Bottleneck grade: 🔴×≥4 → S-grade (single-point failure, highest priority); 🔴×3 → A-grade (severely constrained); 🔴×1-2 → B-grade (stressed but manageable); no 🔴 → not a bottleneck, skip.

Step 4: Company Screening — From Bottleneck to Tickers

For each S/A-grade bottleneck, use web_search / screen_market to find listed companies.

Initial Screen

Criterion	Requirement
Listing status	Listed (A/HK/US/JP/TW/EU)
Bottleneck revenue share	>30% of revenue from the bottleneck link
Market cap	Prefer <$10B (large caps already priced)
Liquidity	Average daily turnover >$1M

Valuation Gate (mandatory, never skip)

A real bottleneck ≠ an investment opportunity. For every company, compute PE/PB/ROE/FCF yield with financial_rigor (command=verify_valuation), and run financial_rigor (command=three_scenario) for scenario valuation:

• Red light (any one → signal strength capped at ★★, flag "valuation stretched"): market cap >20% of TAM; PS>30x with revenue growth <100%; market cap >10× 5-year optimistic revenue forecast; stock doubled within 60 days of a follow-on offering.
• Yellow light (needs extra justification, else downgrade): loss-making + PS>15x; PS >5× a profitable peer; PE>80x (compute PEG).
• Green light (bonus): PS<10x with revenue growing; PE<30x with a moat (flag "margin of safety").

Sanity check (mandatory): with financial_rigor (command=three_scenario), answer — "buying at current market cap, if the most optimistic scenario fully plays out and I exit at 25× PE in 10 years, what's the annualized return?" <10%/yr → flag "no margin of safety at current price".

Step 5: Cross-Validation — Don't Trust a Single Story

Positive checks

Check	Question
Customer validation	Have top customers signed/imported? (check announcements, customer filings)
Revenue validation	Is the bottleneck already showing in revenue growth? (last 2-3 quarters)
Price validation	Is the product raising price? (industry quotes, analyst reports)
Capacity validation	Is capacity really tight? (lead times, customer complaints)
Capital validation	Is there expansion capex? (company guidance)

Use get_financial_statements / get_stock_news / web_search.

Reverse checks (Munger inversion)

• Why don't smart people buy this stock?
• Can the bottleneck be bypassed? Alternative routes?
• Can China / other players quickly replicate capacity?
• If end-demand drops 50%, what happens to this company?
• Has management diluted at highs before?
• What growth assumption does the current valuation imply?

Step 6: Output — Bottleneck Opportunity Board

Ranking Table

Rank	Company	Ticker	Mkt Cap	Revenue	PS	PE	Bottleneck link	Grade	Share	Growth	Signal	Valuation

Market cap, revenue, PS, PE are mandatory — never skip with "TBD". If financials can't be obtained, signal strength ≤★★.

Signal strength (valuation gate directly affects):

• ★★★★★ multi-cross-validated + customers imported + revenue confirmed + valuation green
• ★★★★ most checks pass + valuation green/yellow (with explanation)
• ★★★ logic holds but parts unverified + valuation yellow acceptable
• ★★ early signal, or logic holds but valuation red
• ★ pure concept, unverified

After drafting, run report_audit (command=extract → verify each point → command=verdict) as a quality gate to ensure no hallucinated numbers.

One-Pager Template

🎯 {Company} ({Ticker}) — {one-line bottleneck positioning}

Why it's a bottleneck: (2-3 sentences)
Why this company: (2-3 sentences)

Catalyst timeline:
- Near-term (1-3m): [earnings / capacity / customer win]
- Mid-term (3-12m): [industry trend / expansion node]

Key risks: 1.  2.

Key data: market cap / revenue / PS / PE / growth / bottleneck revenue share
Margin of safety: 10y 25× PE exit method, annualized return XX%. Conclusion: yes/no.

Cross-validation status: ✅ customer / ✅ revenue / ⚠️ valuation stretched / ❌ unverified

Conclusion: deep research / watchlist / skip

Save with write_file to the reports directory (e.g. reports/bottleneck-map/{trend}-bottleneck-{YYYYMMDD}.md).

Step 7: Inventory Update — Maintain the Bottleneck Map

On each run: ① re-check identified bottlenecks (new suppliers? capacity expanded? substitute breakthrough?); ② scan new bottlenecks (web_search last 7 days supply chain / shortage / bottleneck news); ③ update grades (upgrade/downgrade/relieve).

AI Research Bias Self-Check

Bias	Symptom	Counter
Leader-bias	Search dominated by large caps	Deliberately search small-cap suppliers, add "small cap"
English-bias	Miss JP/KR/TW players	Must search JP/KR/TW market suppliers
Narrative-bias	Drawn to "AI concept" labels	Look only at actual supply-chain position, not market labels
Confirmation-bias	After finding a bottleneck, only seek positive evidence	Force Step 5 reverse checks
Recency-bias	Rely on stale info	Prefer last 30 days of data

Core Principles (highest priority)

1. Don't ask the AI to recommend stocks — ask it to decompose supply chains. The question matters more than the answer.
2. Physical first — only links that need real physical product/material/equipment.
3. Layer 2 and Layer 3 — don't chase already-priced leaders.
4. Cross-validate — every conclusion needs ≥2 independent sources.
5. Be honest about uncertainty — if data is missing, say so; don't fill with speculation.
6. Bottlenecks are temporary — every bottleneck gets resolved; the key is timing the window.
7. Small cap ≠ good opportunity — a small cap can also be a bad company; it must pass financial quality.
8. A real bottleneck ≠ an investment — at PS>30x or still loss-making, the current price is not a buy. Valuation is a hard gate that cannot be overridden by bottleneck purity, signal strength, or narrative appeal. Better to miss a bottleneck stock that ran than buy a loss-making company at 100× sales.