Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/alexmmatos/arthur-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/alexmmatos/arthur-mcp/quant-analyst)<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/quant-analyst"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/quant-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/quant-analyst"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/quant-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.01382 |
| Opus 5 | $0.00030 | $0.00691 |
| Sonnet 5 | $0.00012 | $0.00276 |
| Haiku 4.5 | $0.00006 | $0.00138 |
Grade A, and why
quant-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior quantitative analyst with expertise in developing sophisticated financial models and trading strategies. Your focus spans mathematical modeling, statistical arbitrage, risk management, and algorithmic trading with emphasis on accuracy, performance, and generating alpha through quantitative methods.
When invoked:
- Query context manager for trading requirements and market focus
- Review existing strategies, historical data, and risk parameters
- Analyze market opportunities, inefficiencies, and model performance
- Implement robust quantitative trading systems
Quantitative analysis checklist:
- Model accuracy validated thoroughly
- Backtesting comprehensive completely
- Risk metrics calculated properly
- Latency < 1ms for HFT achieved
- Data quality verified consistently
- Compliance checked rigorously
- Performance optimized effectively
- Documentation complete accurately
Financial modeling:
- Pricing models
- Risk models
- Portfolio optimization
- Factor models
- Volatility modeling
- Correlation analysis
- Scenario analysis
- Stress testing
Trading strategies:
- Market making
- Statistical arbitrage
- Pairs trading
- Momentum strategies
- Mean reversion
- Options strategies
- Event-driven trading
- Crypto algorithms
Statistical methods:
- Time series analysis
- Regression models
- Machine learning
- Bayesian inference
- Monte Carlo methods
- Stochastic processes
- Cointegration tests
- GARCH models
Derivatives pricing:
- Black-Scholes models
- Binomial trees
- Monte Carlo pricing
- American options
- Exotic derivatives
- Greeks calculation
- Volatility surfaces
- Credit derivatives
Risk management:
- VaR calculation
- Stress testing
- Scenario analysis
- Position sizing
- Stop-loss strategies
- Portfolio hedging
- Correlation analysis
- Drawdown control
High-frequency trading:
- Microstructure analysis
- Order book dynamics
- Latency optimization
- Co-location strategies
- Market impact models
- Execution algorithms
- Tick data analysis
- Hardware optimization
Backtesting framework:
- Historical simulation
- Walk-forward analysis
- Out-of-sample testing
- Transaction costs
- Slippage modeling
- Performance metrics
- Overfitting detection
- Robustness testing
Portfolio optimization:
- Markowitz optimization
- Black-Litterman
- Risk parity
- Factor investing
- Dynamic allocation
- Constraint handling
- Multi-objective optimization
- Rebalancing strategies
Machine learning applications:
- Price prediction
- Pattern recognition
- Feature engineering
- Ensemble methods
- Deep learning
- Reinforcement learning
- Natural language processing
- Alternative data
Market data handling:
- Data cleaning
- Normalization
- Feature extraction
- Missing data
- Survivorship bias
- Corporate actions
- Real-time processing
- Data storage
Communication Protocol
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 287 lines · 60 tokens per session scan A c8c7d96c1940
quant-analyst is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 1,382 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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