What problem does it solve? Investors chasing obvious mega-trends like AI infrastructure often arrive after first-layer winners (GPUs, HBM) are fully priced. This Skill systematically decomposes a super-trend into its physical supply chain layers to find second- and third-tier bottleneck components where pricing power and alpha still exist. ## Core Features & Use Cases - Supply Chain Decomposition: Breaks a confirmed super-trend (AI infrastructure, energy transition, defense, semiconductors, space) into Layer 0-4 physical components and scores each link against six bottleneck criteria (supplier concentration, expansion lead time, substitutability, utilization, demand growth, customer qualification cycles). - Company Screening with Valuation Gates: Maps S/A-grade bottlenecks to listed companies across A-share, HK, US, JP, TW, and EU markets, then enforces mandatory PS/PE valuation red-yellow-green light checks so a real bottleneck never overrides an overextended price. - Cross-Validation & Hourly Scan Mode: Requires at least two independent sources per conclusion, runs Munger-style reverse verification, and supports a scheduled hourly mode that only writes reports to reports/bottleneck-map/ when new signals or actionable tickers appear. - Use Case: Ask it to scan the AI infrastructure trend; it produces a bottleneck map highlighting, for example, InP substrates or optical modules as S-grade constraints, then outputs a ranked table of small-cap suppliers with valuation safety-margin calculations. ## Quick Start Run the bottleneck-hunter skill on the AI infrastructure trend to produce a supply chain bottleneck map and a ranked list of investable companies with valuation checks.
