| name | scan-value-chain |
| description | 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.
|
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, alice rss grep
for the news cluster. (See the alice, alice-analysis, traderhub skills.)
- 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.
- 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.
- 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.
- 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.
- 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/<name>.md grow
later as specific names get researched. The next session reads shortlist.md
and continues — never a cold start.
