Research tool only. Company names mentioned are for educational and analytical purposes — not recommendations to buy, sell, or hold any security. Ameya Pimpalgaonkar is not a SEBI registered investment advisor or research analyst. Read full disclaimer →

Claude Cowork Plugin · Free · v3.2.1

Most people read the headline.
We read the value chain.

Turn any technology signal, global event, or market theme into a structured layer-by-layer breakdown — through conversation, not summaries.

6
Framework layers
18
Ready scenarios
17
Connectors
MIT
Open source
Live decomposition — AI Inference Demand
L0SignalWhy inference is the battleground
L1MechanicsWhat inference actually requires
L2Cause TreeStructural drivers of demand
L3Solution SpaceChip, cloud, model industries
L4Build RequirementsCompute, memory, power, cooling
L5Value Chain ActorsGlobal + India proxies
L6Research LandscapeHow to access this space
L5 → NvidiaAMDAWS 🇮🇳 Tata Elxsi🇮🇳 KPIT

Surface reaction vs structured understanding

Most people react to signals. Curiosity Stack turns any signal into a structured, layer-by-layer business insight.

Without Curiosity Stack

Read the headline — form a vague impression, move on

Miss the non-obvious businesses buried in the chain

React when it's already priced in or covered

Can't explain the second and third order effects

With Curiosity Stack

Understand why the signal matters — and why now

Find non-obvious businesses at each layer of the chain

Identify India's specific position in the chain

Walk away with a structured, shareable research brief

Six layers. One method. Any signal.

One question at a time. You build the understanding yourself. That's the point.

L0
Signal
What's happening and why now?
L1
Mechanics
What is this really at a technical level?
L2
Cause Tree
Root causes — structural vs cyclical?
L3
Solution Space
What industries does each cause create?
L4
Build Requirements
What inputs and infrastructure?
L5
Value Chain Actors
Who does this — global and India?
L6
Research Landscape
How is this space typically accessed?

"The intent is not to reach the end of the process but to go through the process itself."

18 topics ready to decompose

Not sure where to start? Browse pre-built scenarios across six categories. Each launches a full six-layer decomposition with one click inside the plugin.

See a real decomposition

Three real scenarios — exactly as the plugin generates them.

Geopolitics

Middle East conflict → oil supply chain

How escalation travels through the global oil value chain — who wins, who loses, where India sits.

L0
Signal
Strait of Hormuz carries 21% of global oil. Any disruption = immediate price shock.
L1
Mechanics
India imports 85% of crude. $10/barrel spike adds ~₹83,000 crore to the import bill.
L2
Cause Tree
Structural: geographic concentration. Cyclical: current geopolitical tension.

+ L3 Solution Space, L4 Build Requirements, L6 Research Landscape inside the plugin

Value Chain Output — L5 Actors
Global
Saudi AramcoADNOCVitol
Refining
🇮🇳 Reliance🇮🇳 IOC🇮🇳 BPCL
Logistics
Frontline🇮🇳 SCITrafigura
Renewables
🇮🇳 Adani Green🇮🇳 NTPC🇮🇳 Waaree
Non-obvious insight: Renewable companies are paradoxical beneficiaries — each oil spike compresses the payback period on solar and wind.
AI — Global

AI inference demand — the next battleground

Training is won. Inference is what happens when billions of people use AI models every day.

L0
Signal
ChatGPT serves 100M+ users daily. Each query costs ~10x a Google search. Inference is the new infrastructure.
L1
Mechanics
Inference requires different hardware than training — lower latency, higher throughput, different memory profile.
L2
Cause Tree
Structural: AI PMF confirmed. Cyclical: GPU shortage accelerates custom silicon.

+ L3 Solution Space, L4 Build Requirements, L6 Research Landscape inside the plugin

Value Chain Output — L5 Actors
Chips
Nvidia H100AMD MI300Google TPU
Memory
SK HynixMicronSamsung
Packaging
TSMC CoWoS🇮🇳 Tata Elxsi🇮🇳 KPIT
Cooling
VertivSchneider🇮🇳 Airedale
Non-obvious insight: Advanced packaging (OSAT) is the layer most investors miss. TSMC's CoWoS packaging is as much a bottleneck as the GPU itself.
AI — India

Indian IT services in the AI era

AI is automating the work Indian IT services companies sell. Where does opportunity actually sit?

L0
Signal
TCS, Infosys, Wipro all launching AI practices — while traditional services demand softens.
L1
Mechanics
IT services = arbitrage of Indian talent vs Western costs. LLMs now do 30-40% of that work at near-zero marginal cost.
L2
Cause Tree
Structural: LLM capability crossed the routine services threshold. Cyclical: client IT budgets under pressure.

+ L3 Solution Space, L4 Build Requirements, L6 Research Landscape inside the plugin

Value Chain Output — L5 Actors
Legacy IT
🇮🇳 TCS🇮🇳 Infosys🇮🇳 Wipro
AI-native
🇮🇳 Persistent🇮🇳 MphasisAccenture AI
GCC
🇮🇳 Nasscom GCCsJP Morgan India
Data layer
🇮🇳 iMerit🇮🇳 Appen IndiaScale AI
Non-obvious insight: The data annotation layer is India's emerging advantage — same talent pool that built IT services can build the human-in-the-loop layer AI depends on.

Everything in one plugin

Skills, agents, and connectors. Install once. Works with your existing sources.

Core feature
Animated Value Chain
Layer-by-layer animated diagram after every decomposition. Global companies and India proxies in separate columns.
  • Slides in layer by layer on generation
  • India proxies with distinct visual treatment
  • ⬡ Attribution badge on every output
Autonomous agent
India Proxy Agent
Give it any global company or theme. Independently searches Tracxn, Inc42, Screener.in, NASSCOM — returns a validated shortlist.
  • Fully autonomous — no input needed after trigger
  • Direct / Supplier / Beneficiary / Enabler patterns
  • Validation signals and watch triggers per company
Automated monitoring
Watchlist + Trigger Alerts
Weekly / daily digest to Gmail, plus layer-specific triggers that fire only when a precise condition is met.
  • Cadence digest: weekly, daily, fortnightly
  • "Alert me when Layer 4 of EV batteries changes"
  • HIGH / MEDIUM / LOW materiality scoring
New in v3.2.1
Scenario Library
18 pre-built topics across 6 categories. Preview all 6 layer hints before committing. One click launches the full decomposition.
  • India · Geopolitics · AI · Cybersecurity · Energy
  • AI drills to Global AI and India AI
  • One click to launch full decomposition

Watch it work

Real plugin sessions. See the Socratic conversation, layer cards, and final value chain output.

Video coming soon

Core feature
Full 6-Layer Decomposition — Semiconductor Packaging
Signal to animated Value Chain output. ~10 min.

Video coming soon

Autonomous agent
India Proxy Agent — Finding Indian Equivalents of Nvidia
Live autonomous search with validated shortlist. ~6 min.

Video coming soon

Monitoring
Watchlist Tracker — Setting a Layer 4 Trigger Alert
Configure EV battery monitoring with a layer trigger. ~5 min.

Video coming soon

New in v3.2.1
Scenario Library — Browse and Launch in One Click
18 ready-made topics, one-click decomposition launch. ~4 min.

Built for two kinds of thinkers

📊
Investors and researchers
Retail investors · Analysts · Fund researchers
Find non-obvious businesses before they're covered, before they're priced in. From vague signal to named companies at each layer — India proxies flagged specifically.
🏢
Enterprise professionals
Strategy · Business development · Product · Consulting
Understand where AI and technology are actually going — not just the headline, but the business implications, the value chain, the India angle.

Free. Open source.
Install in 2 minutes.

Download from GitHub and install directly in Claude Cowork. MIT licensed — inspect, fork, and customise freely.

v3.2.1MIT LicenseClaude Cowork29 files17 connectors
Download v3.2.1 from GitHub
1
Download the plugin
Click the button → download curiosity-stack-v3.2.1.zip
2
Open Claude Cowork
Claude Desktop → Cowork tab → Customize → Browse Plugins
3
Upload the zip
Upload custom plugin → select zip → installs immediately
4
Run setup
Type /curiosity-stack:setup — 2 minutes — then describe any topic
Important disclaimer

Curiosity Stack is a structured research and educational tool only. All company names, sectors, industries, and value chain references mentioned within the plugin or on this website are cited purely for analytical, educational, and informational purposes.

Nothing on this website or produced by the Curiosity Stack plugin constitutes investment advice of any kind, a research report under SEBI (Research Analysts) Regulations 2014, a buy/sell/hold recommendation for any security or financial instrument, or a solicitation to transact in any financial product.

Ameya Pimpalgaonkar is not a SEBI registered investment advisor or research analyst. The identification of companies at layers of a value chain is an analytical exercise only — it does not imply any view on the investment merits of those companies. Always consult a SEBI registered advisor before making any investment decision.