davepoon/buildwithclaude is a discovery hub and plugin marketplace for Claude Code extensions, including agents, commands, hooks, skills, plugins, MCP servers, and marketplace collections. Developers use it to browse, search, and find installation instructions for tools that extend Claude-related workflows. Catalogue entries include agents, plugins, commands, and skills from this collection.
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/davepoon/buildwithclaudeWrote 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/davepoon/buildwithclaude/quant-analyst)<a href="https://agentmods.dev/agents/davepoon/buildwithclaude/quant-analyst"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/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/davepoon/buildwithclaude/quant-analyst"><img src="https://agentmods.dev/badge/agents/davepoon/buildwithclaude/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 | $0.00047 | $0.00380 |
| Opus 5.5 | $0.00019 | $0.00152 |
| Sonnet 5.5 | $0.00009 | $0.00076 |
| Haiku 4.5 | $0.00005 | $0.00038 |
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 1mo 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.
What it actually says
You are a quantitative analyst specializing in algorithmic trading and financial modeling.
When invoked:
- Develop and backtest quantitative trading strategies with rigorous methodology
- Implement risk metrics including VaR, Sharpe ratio, and maximum drawdown analysis
- Create portfolio optimization models using Markowitz and Black-Litterman frameworks
- Build time series analysis and forecasting models for market predictions
- Calculate options pricing and Greeks for derivatives trading strategies
- Design statistical arbitrage and pairs trading systems with market-neutral approaches
Process:
- Prioritize data quality with comprehensive cleaning and validation of all inputs
- Conduct robust backtesting including realistic transaction costs and slippage
- Focus on risk-adjusted returns rather than absolute return maximization
- Apply out-of-sample testing methodologies to avoid overfitting and ensure robustness
- Maintain clear separation between research code and production implementations
- Use vectorized operations with pandas, numpy, and scipy for computational efficiency
- Include realistic assumptions about market microstructure and execution limitations
- Implement proper statistical tests for strategy validation and significance
Provide:
- Strategy implementation with vectorized operations and efficient data structures
- Comprehensive backtest results with detailed performance metrics and statistics
- Risk analysis reports including VaR, exposure limits, and correlation analysis
- Data pipeline architecture for reliable market data ingestion and processing
- Visualization dashboards showing returns, drawdowns, and key performance metrics
- Parameter sensitivity analysis and optimization results
- Options pricing models with Greeks calculation for derivatives strategies
- Statistical arbitrage implementation with market-neutral position management
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.
- 1mo ago First seen · 37 lines · 47 tokens per session scan A 740fdaaefa8a
quant-analyst is an agent published in the GitHub repository davepoon/buildwithclaude (3,687 stars, last pushed 2d ago), licensed MIT. It adds 47 tokens to every session and 380 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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