An advanced analytics engine for the TRON network that transforms raw on-chain data into actionable insights and comprehensive health reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install trongrid-data-insights
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 trongrid-data-insights 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 TronGrid Data Insights?
TronGrid Data Insights is a high-performance analytics skill designed to provide a deep-dive into the TRON blockchain ecosystem. By leveraging the TronGrid MCP server, it aggregates complex data points including transaction volumes, contract interactions, and governance metrics to produce a human-readable snapshot of network health. It is an essential tool for developers, analysts, and stakeholders who need to monitor the pulse of the TRON network without manual data mining.
This skill automates the extraction of block-level details, categorizes transaction types, and identifies trending tokens and hot contracts. Whether you are tracking TRX burn rates or analyzing the efficiency of Super Representatives, this integration provides the technical depth required for professional-grade blockchain monitoring through Openclaw Skills.
TronGrid Data Insights Use Cases
- Generating real-time TRON network health dashboards and daily activity reports.
- Identifying trending TRC-20 tokens and high-traffic smart contracts for market research.
- Monitoring network resource economics, including energy and bandwidth price fluctuations.
- Auditing the most active accounts to distinguish between exchange activity, whales, and automated bots.
- Tracking governance status and Super Representative performance metrics.
How TronGrid Data Insights Works
- The skill initiates a network snapshot by fetching current block height, chain parameters, and node synchronization status.
- It performs iterative block analysis, retrieving the last 20 blocks to calculate average transaction density and success rates.
- Data is categorized into transaction types such as TRX transfers, smart contract calls, and staking operations.
- It aggregates contract interactions to identify 'hot' addresses and fetches metadata for trending tokens via TRC-20 info lookups.
- Governance data is pulled from the witness list to evaluate voting distribution and block production efficiency.
- Finally, the skill compiles all metrics into a structured Insights Report with key takeaways and trend analysis.
TronGrid Data Insights Setup
To utilize this skill, you must have the TronGrid MCP server configured. Follow these steps to integrate with your Openclaw Skills environment:
- Obtain a TronGrid API Key from the TronGrid Dashboard.
- Install the MCP server following the official guide.
- Configure your environment variables:
export TRONGRID_API_KEY="your_api_key_here"
- Add the
trongrid-data-insightsskill to your agent's configuration file to enable the analytics workflow.
TronGrid Data Insights Data Schema & Taxonomy
The skill organizes TRON data into a multi-dimensional taxonomy for clear reporting:
| Category | Metrics Tracked | Data Source |
|---|---|---|
| Network | Block Height, Daily Tx Volume, Burn Rate | getBlock, getBurnTrx |
| Activity | Success Rate, Avg Block Time, Tx Types | getTransactionInfoByBlockNum |
| Assets | Token Transfers, Symbol, Metadata | getTrc20Info, getEventsByLatestBlock |
| Governance | SR Votes, Witness List, Node Count | getPaginatedNowWitnessList |
| Resources | Energy Price, Bandwidth Price | getEnergyPrices, getBandwidthPrices |
TronGrid Data Insights Advanced Features
- Multi-block iterative auditing for high-precision transaction success rate calculation.
- Automated categorization of account types (Exchange vs. Bot vs. Whale) using account metadata.
- Real-time resource economic tracking to predict energy and bandwidth cost trends.
- Parallelized data fetching across multiple MCP endpoints for reduced latency.
- Adaptive error handling that adjusts sample sizes during periods of high network congestion.
SKILL.md
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