Borrowing it
Nothing to install: this file belongs to StanleyChanH/SharpETF. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/StanleyChanH/SharpETF/master/CLAUDE.mdgit clone --depth 1 https://github.com/StanleyChanH/SharpETFWrote 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/instructions/stanleychanh/sharpetf/claude-md)<a href="https://agentmods.dev/instructions/stanleychanh/sharpetf/claude-md"><img src="https://agentmods.dev/badge/instructions/stanleychanh/sharpetf/claude-md/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/instructions/stanleychanh/sharpetf/claude-md"><img src="https://agentmods.dev/badge/instructions/stanleychanh/sharpetf/claude-md.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 | $0.03256 | $0.03256 |
| Opus 5.5 | $0.01302 | $0.01302 |
| Sonnet 5.5 | $0.00651 | $0.00651 |
| Haiku 4.5 | $0.00326 | $0.00326 |
Grade A, and why
SharpETF CLAUDE.md 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 2mo 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
This is an enhanced ETF Sharpe ratio optimization system (增强版ETF投资组合优化系统) that provides comprehensive quantitative investment decision support. It uses Tushare API to fetch ETF data and implements multiple optimization strategies including Sharpe ratio maximization, risk parity, and multi-objective optimization. The system features ETF Chinese name support, complex growth prediction, and professional HTML report generation. Written in Python and targets Chinese-speaking quantitative finance community.
Latest Enhancements (v2.3.0 - Code Refactoring)
Major Refactoring
- Unified Optimization Engine: Merged CVXPY and SciPy portfolio optimizers into a single module with automatic backend selection
- Unified Quantitative Signals: Integrated simple and advanced quantitative signal modules with mode switching support
- Code Optimization: Reduced from 21 files to 19 files (-9.5%) and 10,047 lines to 9,564 lines (-4.8%)
- Eliminated Redundancy: Removed duplicate modules, backup files, and streamlined imports
- Architecture Enhancement: Improved error handling, backward compatibility, and maintainability
Technical Improvements
- Smart Backend Selection: Automatic detection and fallback between CVXPY and SciPy optimizers
- Mode-based Signal Processing: Support for simple/advanced/auto modes in quantitative signal generation
- Enhanced Error Handling: Robust fallback mechanisms and comprehensive exception handling
- Streamlined Dependencies: Simplified import structure and reduced module interdependencies
- Code Quality: Enhanced readability, maintainability, and architectural consistency
Verified Functionality
- Full Testing: Successfully tested in conda environment with all core features working
- Backward Compatibility: All original functionality preserved with consistent APIs
- Performance: Intelligent backend selection improves computational efficiency
- Robustness: Enhanced error handling ensures system stability
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.
- 2mo ago First seen · 301 lines · 3,256 tokens per session scan A 718af616758d
SharpETF CLAUDE.md is an instructions file published in the GitHub repository StanleyChanH/SharpETF (11 stars, last pushed 1y ago), licensed MIT. It adds 3,256 tokens to every session, about $0.0130 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.
SharpETF CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| SharpETF CLAUDE.mdStanleyChanH/SharpETF | Instructions file | 11 | 1y ago | MIT | A | 3,256 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
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| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |