# Scan Value Chain > Scan an investment theme by decomposing its value chain, then surface the handful of names actually worth researching — each with why and the next question. Use when the user has a theme/sector/thread but no specific ticker yet: "what's worth looking at in semis", "scan the AI-infra space", "I'm curious about uranium / obesity drugs / power grid", "who are the picks-and-shovels in X", "map the supply chain for Y", "find the names worth watching in the X value chain". This is the have-a-theme / no-target step — it turns "I don't know what to look at" into a short, reasoned shortlist. - Skill: `traderalice/scan-value-chain` (Agent Skill) - Install (CLI): `npx skillmds@latest add traderalice/scan-value-chain` - Raw SKILL.md: https://api.skillmd.com/api/skills/traderalice/scan-value-chain/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: TraderAlice (https://skillmd.com/u/traderalice) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/traderalice/scan-value-chain --- # Scan a theme by its value chain Turn a theme the user can't yet act on into a short list of names worth digging into. The point is NOT a data dump — it's "where is the interesting thing, and why." ## Procedure (don't answer from memory — go to the data) The data is on your CLIs: `alice market search` to turn a name into a barId, `traderhub equity` / `traderhub board` for valuation snapshots & macro, `alice analysis quant` for where each trades vs its own trend. Choose news sources to suit the question. (See the `alice`, `alice-analysis`, `traderhub` skills.) 1. **Decompose the chain, not a flat list.** Break the theme into structural layers — upstream (inputs, equipment, IP) → midstream (manufacture, core product) → downstream (demand, end-market). Place the real names in each layer. The value is the structure itself: who supplies whom, where the margin/bottleneck sits, who's a picks-and-shovels play. This is the meta-method — apply it to ANY theme, don't hardcode one taxonomy. 2. **Quick read per node.** Across the candidates, pull a quick read from the data: a valuation snapshot, any near-term catalysts, and where each trades vs its own trend (stretched or basing). Wide and cheap — you're triaging, not deep-diving. 3. **Find the divergence.** Surface 3–6 names where there's something to pull on: cheap vs its layer, margin shifting along the chain, a catalyst close, a leader/laggard gap. Drop the rest — a scan that returns everything returns nothing. 4. **Frame the top-down driver.** Is the theme live right now? Tie it to macro — the rate/capex cycle, energy, any news cluster around the theme — the macro frame is what separates a live theme from noise. 5. **Hand off to research.** For each surfaced name: one-line WHY + the next question to answer (the "is the thesis real" question). That next question is the baton to the deeper research step — the `build-thesis` skill. ## Output — persist as a file group, don't leave it in chat Workspace sessions can be destroyed at any time; anything not written to a file is lost. And coding-ifying the workflow is core to this project — research that produces no files is a contradiction. So the result of a scan must land in files. - **First time on a theme:** propose a small file/directory layout and confirm it with the user before writing — the shortlist, per-name notes, the chain map, whatever this theme needs. Don't hardcode a layout from this skill; settle the shape WITH the user, per theme. - **After that:** the agreed file group IS the dossier. Every session just CRUDs it — read it, update it, add to it. File-based, git-trackable, survives session loss. That's the coding workflow. The shortlist and the per-name "next question" from the procedure above are what get written down — so the next session starts from them, not from zero. ## Worked example: semiconductors One theme, worked end to end. Decompose freshly for any other theme — don't pattern-match these layers (a drug theme, say, layers differently: discovery / developer → CDMO manufacturing → distribution / PBM → payer). **Decompose the chain** (representative names, not exhaustive): - **Upstream — tools & IP** (most concentrated moats): - EDA / IP: Cadence (CDNS), Synopsys (SNPS), Arm (ARM) - Equipment (WFE): ASML (ASML — sole EUV supplier), Applied Materials (AMAT), Lam (LRCX), KLA (KLAC), Tokyo Electron (8035.T) - Materials: wafers (Shin-Etsu, SUMCO), photoresist / specialty chemicals - **Midstream — make & design:** - Foundry (pure-play make): TSMC (TSM), GlobalFoundries (GFS), SMIC - IDM (design + make): Intel (INTC), Samsung, Texas Instruments (TXN) - Fabless (design only): NVIDIA (NVDA), AMD (AMD), Broadcom (AVGO), Marvell (MRVL), Qualcomm (QCOM) - Memory: Micron (MU), SK Hynix, Samsung — DRAM / NAND / **HBM** - Packaging & test (OSAT): ASE (ASX), Amkor (AMKR) — **advanced packaging** - **Downstream — demand:** hyperscalers (MSFT / GOOGL / META / AMZN — also rolling their own silicon: TPU, Trainium, MTIA, Maia), devices (AAPL), auto / industrial, servers (SMCI, DELL) **Where the tension is right now** — this is what a scan surfaces, not the full roster: the binding constraint for AI silicon has migrated from leading-edge logic to **HBM + advanced packaging (CoWoS)**, so Micron / SK Hynix and TSM's CoWoS capacity + Amkor deserve more attention than the headline GPU names. ASML is the single most concentrated upstream choke point. **Top-down frame:** semis run on three clocks — hyperscaler **capex**, the **rate** cycle (long-duration growth multiples), and the **memory inventory / pricing** cycle. Tie the scan to these via the macro and news data. **Proposed file structure** (confirm / adjust with the user — don't impose): ``` semis/ map.md # chain decomposition + where the tension sits + macro frame shortlist.md # the 3–6 names to dig now: one-line why + next question each notes/ # per-name research, added as you climb scan → thesis (R3+) NVDA.md MU.md ... ``` `map.md` and `shortlist.md` are produced by this scan; `notes/.md` grow later as specific names get researched. The next session reads `shortlist.md` and continues — never a cold start.