Smart money intelligence for AI agents using the Fomo social graph to track top crypto traders.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install fomo-research
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install fomo-research using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Fomo Research?
The Fomo Research skill empowers your AI agent with institutional-grade smart money intelligence by tapping into the fomo.family social graph. It allows agents to monitor on-chain wallet activity across Solana and Base, providing insights into what profitable traders are buying and selling in real-time. By integrating this Openclaw Skills extension, developers can build agents that identify market trends, track whale movements, and synthesize trading theses directly from the blockchain.
This skill bridges the gap between social sentiment and on-chain reality, providing a structured way to follow top performers. Whether you are building a personal trading assistant or a market research bot, this tool provides the raw data and aggregated analytics needed to understand professional crypto trader behavior.
Fomo Research Use Cases
- Monitoring elite trader activity and whale wallet movements on Solana and Base.
- Identifying trending tokens based on unique buyer counts from tracked handles.
- Detecting market convergence when multiple top traders buy the same asset.
- Generating daily trading summaries and profit/loss reports for specific watchlists.
- Researching the underlying thesis and sentiment behind specific token purchases.
How Fomo Research Works
- The agent registers with the Cope API to obtain a unique API key for secure authentication.
- A watchlist is created, either manually or by syncing follows from an existing Fomo social profile.
- The agent polls the activity endpoint to detect new on-chain swaps, buys, and sells in real-time.
- Raw transaction data is filtered by handle, chain, or USD amount to isolate high-conviction signals.
- The skill analyzes individual transactions to compute complete trade cycles, including entry price, exit price, and total profit or loss.
Fomo Research Setup
To get started with this Openclaw Skills tool, follow these steps:
- Register your agent to obtain your API key:
curl -X POST https://api.cope.capital/v1/register \
-H "Content-Type: application/json" \
-d '{"agent_name": "YOUR_AGENT_NAME", "description": "AI trading assistant"}'
Set the
COPE_API_KEYenvironment variable with the key provided in the response (starts withcope_).(Optional) Sync your Fomo profile to import your existing follows into a watchlist:
curl -X POST https://api.cope.capital/v1/account/sync-fomo \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"fomo_handle": "YOUR_USERNAME"}'
Fomo Research Data Schema & Taxonomy
The skill organizes blockchain data into highly actionable entities:
| Entity | Description | Key Metadata |
|---|---|---|
| Activity | Raw on-chain events | action (buy/sell), usd_amount, token_mint, chain |
| Trade | Aggregated round-trips | usd_in, usd_out, pnl, open_at, close_at |
| Watchlist | User-defined groups | name, handles (list of tracked traders) |
| Convergence | Shared token interest | mint, symbol, wallets_involved, max_gain_pct |
Fomo Research Advanced Features
- Convergence detection alerts which trigger when multiple elite wallets buy the same token within a short timeframe.
- Poll-to-fetch pattern implementation to minimize API costs by only fetching data when new activity is detected.
- x402 payment protocol support for agents requiring unlimited real-time calls and high-volume watchlists.
- Automated leaderboard monitoring to dynamically discover and track new high-PnL traders.
- Deep thesis extraction that connects social commentary with actual on-chain positioning for better sentiment analysis.
SKILL.md
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