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.
npx skills add haiyunsky/hpsilab-quant-finance-mcp --skill stock-researchgit clone --depth 1 https://github.com/haiyunsky/hpsilab-quant-finance-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/skills/haiyunsky/hpsilab-quant-finance-mcp/stock-research)<a href="https://agentmods.dev/skills/haiyunsky/hpsilab-quant-finance-mcp/stock-research"><img src="https://agentmods.dev/badge/skills/haiyunsky/hpsilab-quant-finance-mcp/stock-research/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/skills/haiyunsky/hpsilab-quant-finance-mcp/stock-research"><img src="https://agentmods.dev/badge/skills/haiyunsky/hpsilab-quant-finance-mcp/stock-research.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 | $0.00067 | $0.00466 |
| Opus 5.5 | $0.00027 | $0.00186 |
| Sonnet 5.5 | $0.00013 | $0.00093 |
| Haiku 4.5 | $0.00007 | $0.00047 |
Grade A, and why
stock-research 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 2d 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
Stock research
Use the HPSILab connector's tools. If they are not available, tell the user to connect HPSILab (https://hpsilab.com/connect) and stop; never invent figures. Pass one official ticker per call, and use the parameter names in each tool's own input schema (some take symbol, some take ticker).
Pick the tools that answer the question:
| The user wants | Call | Horizon to state |
|---|---|---|
| A general view, "analyze X" | analyze_stock |
mixed; name each part's source |
| A likely price range | get_monte_carlo |
the next 10 trading days |
| The model's direction | get_ai_prediction |
the next trading day only |
| How the strategy has done | get_equity_curve |
historical backtest, not a forecast |
| Chart images | generate_stock_images |
the data date |
| A written report | generate_stock_research_report |
the data date |
For an open-ended "analyze X", start with analyze_stock, then add get_monte_carlo for the range. Keep each number with its own horizon; never move a figure from one horizon to another.
generate_stock_images and generate_stock_research_report create hosted files and use the user's plan quota, so confirm before calling them unless the user asked for charts or a report, and do not retry them automatically.
When you answer, separate what the tools returned from your interpretation, list the strongest points on each side, and give the data date. If a tool fails or is gated, say which one and why, and continue with the others. Do not tell the user to buy or sell, and do not present a range or a probability as a guarantee. Never ask for, print or store an API key.
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.
- 2d ago First seen · 26 lines · 67 tokens per session scan A b161fc8bfdd8
stock-research is a skill published in the GitHub repository haiyunsky/hpsilab-quant-finance-mcp (1 stars, last pushed 2d ago), licensed MIT. It adds 67 tokens to every session and 466 once invoked, about $0.0003 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 2026-10-25.
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