Connect OpenClaude and Hermes Agents to CoinQuant

CoinQuant is now available as a native agent skill for OpenClaude and Hermes, two popular agent frameworks that allow AI assistants to call external tools and execute multi-step workflows.

With this integration, agents can connect directly to CoinQuant and perform quantitative research tasks autonomously: running backtests, accessing market data, evaluating strategies, and generating insights, all without manual handoffs between tools.

Instead of switching between AI assistants and quantitative research tools, users can now let their agents interact directly with CoinQuant as part of a single workflow.

What's New

CoinQuant can now be registered as a callable skill inside OpenClaude and Hermes agent pipelines. Once connected, agents have direct access to:

• Backtesting: run historical strategy tests with configurable parameters and benchmarks

• Market Data: query price, volume, and derived metrics across assets and time ranges

• Strategy Evaluation: compare strategies by performance, risk, and drawdown

• Quantitative Analysis: apply statistical models and factor analysis within automated workflows

• Research Pipelines: chain multi-step tasks without interruption or manual input
  

  

What Agents Can Do With CoinQuant

Once connected, an OpenClaude or Hermes agent can handle the full quantitative research loop independently.

Run backtests on demand. Agents can specify strategy logic, asset universe, date range, and benchmark, then receive structured results to reason over and act on.

Access and analyze market data. Agents can pull historical OHLCV data, compute momentum, volatility, and drawdown metrics, and run cross-asset comparisons within a single workflow.

Evaluate and rank strategies. Agents can run multiple strategy variants in parallel, rank them by Sharpe ratio, max drawdown, or custom metrics, and surface the strongest candidates.

Execute end-to-end research workflows. Agents can chain tasks, pulling data, running analysis, backtesting a hypothesis, and writing up findings, without human handoffs at any step.

Example Use Cases

1. Backtesting a crypto strategy. A user asks their agent to backtest a momentum strategy on BTC and ETH from 2020–2025 and compare the results against a buy-and-hold benchmark. The agent invokes CoinQuant, runs the analysis, and returns a structured performance summary directly.

2. Morning strategy review. A researcher configures a Hermes agent to rerun a set of strategies each morning with fresh market data and deliver a ranked report before the trading day opens.

3. Building financial AI tools. A developer registers CoinQuant as a core skill in their agent stack and uses the API Agent Skill Pack to prototype and deploy agent-driven research workflows quickly.

Getting Started

The integration is available now for both OpenClaude and Hermes through the CoinQuant API Agent Skill Pack.

1. Download the CoinQuant API Agent Skill Pack

2. Register the CoinQuant skill in your OpenClaude or Hermes agent configuration

3. Authenticate with your CoinQuant API credentials

4. Start calling CoinQuant tools from within your agent workflows

The Skill Pack includes documentation, schema references, and example configurations to get you connected quickly.

Connect OpenClaude and Hermes to CoinQuant

Give your OpenClaude and Hermes agents access to CoinQuant's backtesting, market data, and quantitative research tools.

→ Explore the CoinQuant API Agent Skill Pack

Developers can use the Skill Pack to quickly connect OpenClaude and Hermes agents to CoinQuant workflows, with pre-built configurations ready to deploy.

CoinQuant is now part of the OpenClaude and Hermes ecosystems. Traders, researchers, and developers can use this integration to automate quantitative workflows that previously required manual effort at every step, from data access to backtest execution to strategy evaluation.

If you're building with OpenClaude or Hermes, the CoinQuant skill is ready to connect.

→ CoinQuant API Agent Skill Pack