Borrowing it
Nothing to install: this file belongs to paarths-collab/quant-brain-mcp. 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/paarths-collab/quant-brain-mcp/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/paarths-collab/quant-brain-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/instructions/paarths-collab/quant-brain-mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/paarths-collab/quant-brain-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/paarths-collab/quant-brain-mcp/copilot-instructions.svg" alt="Measured on agentmods" 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 | $0.00332 | $0.00332 |
| Opus 5 | $0.00166 | $0.00166 |
| Sonnet 5 | $0.00066 | $0.00066 |
| Haiku 4.5 | $0.00033 | $0.00033 |
Grade A, and why
quant-brain-mcp copilot-instructions.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 7d 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
Copilot Instructions for Stock Analysis Tools
This project includes a Model Context Protocol (MCP) server that provides advanced financial analysis tools.
When to use MCP Tools
- Use the
generate_optimized_verdicttool whenever a user asks to optimize a portfolio, analyze multiple stocks together, or perform a backtest. - Use the
get_<indicator>tools (e.g.,get_rsi,get_macd) for technical analysis of individual tickers. - Use
fetch_datato get raw OHLCV data.
Tool-Specific Rules
generate_optimized_verdict
- Inputs: List of tickers (e.g.,
["AAPL", "RELIANCE.NS"]), optionalamount, andoptimize_type("mvo" or "hrp"). - HRP: Prefer Hierarchical Risk Parity (
hrp) if the user mentions "low risk" or "risk parity". - Backtest: This tool automatically performs a backtest and returns a Sharp Ratio and Verdict.
Data Types
- Note that all outputs are serialized to standard JSON strings/numbers to avoid
int64errors. - If you encounter a serialization error, suggest the user restart their MCP server in VS Code.
MCP-First Discipline
- For analysis and verdicts, always prefer registered MCP tools over local ad-hoc calculations.
- Do not run custom math snippets if an MCP tool already provides that calculation.
- If an MCP tool fails, clearly mark any local computation as a fallback and recommend rerunning after the MCP issue is resolved.
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.
- 7d ago First seen · 24 lines · 332 tokens per session scan A ae9c387650a0
quant-brain-mcp copilot-instructions.md is an instructions file published in the GitHub repository paarths-collab/quant-brain-mcp (4 stars, last pushed 22d ago), licensed MIT. It adds 332 tokens to every session, about $0.0017 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 2026-08-31.
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