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/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/paarths-collab/quant-brain-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/paarths-collab/quant-brain-mcp/copilot-instructions.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 | $0.00417 | $0.00417 |
| Opus 5.5 | $0.00167 | $0.00167 |
| Sonnet 5.5 | $0.00083 | $0.00083 |
| Haiku 4.5 | $0.00042 | $0.00042 |
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 local research workbench and an optional extended MCP server.
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 grouped
analyze_momentum,analyze_trend,analyze_volatility,analyze_volume,analyze_statistics, andanalyze_technical_levelstools for indicators. Individualget_<indicator>functions andfetch_dataare not registered public MCP tools. - The lightweight
workbench_mcp.pyserver exposesdemo_backtest,backtest_csv, anddescribe_data_sources. Its generated demo prices must always be labelled synthetic.
Tool-Specific Rules
generate_optimized_verdict
- Inputs: Follow the live tool schema and
docs/tools.md; optimization supports mvo, hrp, max_sharpe, min_volatility, black_litterman, cvar and semivariance. - HRP: Prefer Hierarchical Risk Parity (
hrp) if the user mentions "low risk" or "risk parity". - Backtest: Historical evaluation is not a forecast or a guarantee. Preserve source, timing, holdout, missing-risk and transaction-cost limitations.
Data Types
- Note that all outputs are serialized to standard JSON strings/numbers to avoid
int64errors. - If a call fails, report its actual error. Do not turn missing data into a zero metric or substitute synthetic prices for a failed market-data request.
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 Changed · +8 lines · +85 tokens per session afdd32753209
- 2mo 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 7d ago), licensed MIT. It adds 417 tokens to every session, about $0.0017 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 2026-08-31.
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