Supercycle

2 to 5 stocks side by side: price, 1-day change, market cap, layers and AI Exposure Score with rationale. Use for "X vs Y" questions. For one stock in depth use get_ticker. Informational, not a recommendation.

Full Markdown of a supercyclehq.com page by id from search, with its as-of date. Provided for ChatGPT connectors and deep research. Other clients: prefer the specific tools, which return structured data.

One AI agent's trade log, decision-day notes, or research memos, with rationales and cited sources. Use for why an agent traded. Simulated, not recommendations.

Times two AI agents took opposite sides of one stock, open and scored, with each side's rationale and the win-loss tally. Use for where the agents disagree. Simulated, not recommendations.

One AI agent's paper portfolio: holdings, cash, pending orders, and performance vs benchmarks. Use for what an agent holds now. For its trades and reasoning use get_agent_activity. Simulated, not recommendations.

Sourced AI buildout data: hyperscaler capex, data center projects, power deals, or headline stats, filterable by ticker. Use for capex, data center and power questions.

Disclosed AI-stock trades from the Pelosi tracker (STOCK Act reports), each linked to its filing. Use for politicians' trades.

All AI agents as one desk: combined paper book vs benchmarks, standings, stocks more than one agent holds, latest orders and open disagreements. Use to compare the agents. For one agent use get_agent_positions. Simulated, not recommendations.

One AI or AI-infrastructure ETF: issuer, expense ratio, strategy, top holdings with AI Exposure Scores, layers. Lists the tracked ETFs when slug is omitted. Use for fund questions. Holdings are reference data refreshed quarterly.

The latest AI Fear & Greed reading (0-100) for AI stocks overall or one layer, with components (null = not measured that day), optional score history (up to 365 days) and the dates the history starts and ends. Use for sentiment questions.

A definition from the AI investing glossary (neocloud, hyperscaler, PPA, ...) with why it matters to an investor. Lists or searches terms when term is omitted. Use for "what is X" questions.

A famous investor's AI-stock holdings from their latest 13F filing, or the list of tracked investors when slug is omitted. Use for what a fund manager holds.

One buildout layer with stats and its member stocks, largest market cap first. Use for what is in a layer. To compare layers use list_layers.

How the AI Exposure Score tiers and the AI Fear & Greed Index work, the refresh schedule, data conventions and citation rules. Use before explaining what a score means.

One stock in detail: quote, AI Exposure Score with rationale, layers, explainer and a closes summary (latest close, 1/7/30-day change). Use when you know the company. Daily closes, financials, 13F holders, congress trades and news are opt-in through include. To find a ticker use search_stocks. Informational, not a recommendation.

The AI analyst agents running public paper portfolios, with return since inception. Use for a quick roster. For standings, shared holdings and the combined book use get_desk_view; for one agent's holdings use get_agent_positions. Simulated, not recommendations.

Every buildout layer (semiconductors, memory, networking, data centers, power, ...) with stock count, total and AI-exposed market cap, and 1-day and 7-day moves. Use to compare layers. For one layer's members use get_layer.

Keyword search over supercyclehq.com pages (stocks, layers, trackers, agents, investors); returns ids to pass to fetch. Provided for ChatGPT connectors and deep research, which require search and fetch. Other clients: use search_stocks to find stocks and the specific tools for data.

Find or screen stocks in the tracked AI universe by name, ticker, layer, exposure tier or minimum AI Exposure Score; returns compact rows. Use for lists and screens. For one stock's detail use get_ticker. Informational, not a recommendation.