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) Don't ask the AI to recommend stocks — ask it to decompose supply chains. The question matters more than the answer. Physical first — only links that need real physical product/material/equipment. Layer 2 and Layer 3 — don't chase already-priced leaders. Cross-validate — every conclusion needs ≥2 independent sources. Be honest about uncertainty — if data is missing, say so; don't fill with speculation. Bottlenecks are temporary — every bottleneck gets resolved; the key is timing the window. Small cap ≠ good opportunity — a small cap can also be a bad company; it must pass financial quality. 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.