A real-time monitoring dashboard for Uniswap protocol fees that predicts the most profitable moments to execute burns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install monitor-tokenjar
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 monitor-tokenjar 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 Monitor TokenJar?
The Monitor TokenJar skill provides a high-fidelity dashboard for Uniswap's protocol fee system, aggregating data from V2, V3, V4, and UniswapX sources. By integrating this into Openclaw Skills, users gain access to automated projections of fee accumulation rates and real-time profitability analysis. It transforms raw blockchain data into actionable intelligence, answering the critical question of when the next burn will be most profitable for protocol fee seekers.
This skill operates in two distinct modes: a comprehensive one-shot snapshot and a streaming mode for live deposit tracking. By utilizing Openclaw Skills, developers and traders can maintain a competitive edge in the DeFi ecosystem without manually calculating gas costs, UNI price fluctuations, or complex burn thresholds.
Monitor TokenJar Use Cases
- Tracking real-time Uniswap fee accumulation across multiple protocol versions.
- Projecting the specific time or ROI threshold for a profitable burn execution.
- Setting up live alerts for when the TokenJar value exceeds a specific USD threshold.
- Analyzing historical burn frequencies and average profit margins to identify competitive trends.
- Monitoring top fee-generating tokens and shifting market dynamics within the Uniswap ecosystem.
How Monitor TokenJar Works
- The skill initiates parallel data collection calls to fetch current TokenJar balances, Firepit contract states, and accumulation rates.
- It prices all jar assets in USD using real-time market data to calculate the total aggregate value.
- A sub-agent analyzes the data to determine current profitability by comparing the jar value against UNI burn costs and gas estimates.
- If streaming mode is enabled, the skill subscribes to live deposit events, enriching them with running totals and threshold alerts.
- The final output is rendered as a structured dashboard including balances, accumulation trends, burn economics, and future projections.
Monitor TokenJar Setup
To integrate this monitoring capability into your environment, ensure you have the necessary Uniswap MCP tools configured. As part of the Openclaw Skills library, this tool requires an active Ethereum RPC connection and appropriate API keys for price data.
# The skill is activated via natural language within an Openclaw Skills compatible agent
# No manual CLI installation is required if the Uniswap MCP is active.
Monitor TokenJar Data Schema & Taxonomy
| Component | Description | Format |
|---|---|---|
| Current Balances | List of tokens, amounts, USD values, and percentage share. | Markdown Table |
| Accumulation Rates | Daily, weekly, and monthly fee growth estimates based on historical windows. | Key-Value List |
| Burn Economics | Thresholds, UNI prices, gas estimates, total burn cost, and current ROI. | Technical Summary |
| Projection | Estimated time to specific ROI milestones (e.g., 100% ROI). | Predictive Text |
| Live Feed | Timestamped deposit events with running totals and profitability status. | Event Log |
Monitor TokenJar Advanced Features
- Real-Time Streaming: Continuous monitoring of incoming fees for up to 300 seconds per session.
- Profitability Projections: Advanced math logic that predicts the exact timing of a profitable burn based on gas and UNI volatility.
- Custom Alert Thresholds: Trigger specific notifications when the jar reaches a user-defined USD value.
- Competitor Intelligence: Derived frequency analysis to gauge the risk of other searchers executing a burn first.
- Multi-Source Aggregation: Seamlessly combines data from V2, V3, V4, UniswapX, and Unichain native fees into a single view.
SKILL.md
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