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/mindsightventures/lona-agent-skillsWrote 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/rules/mindsightventures/lona-agent-skills/lona-trading)<a href="https://agentmods.dev/rules/mindsightventures/lona-agent-skills/lona-trading"><img src="https://agentmods.dev/badge/rules/mindsightventures/lona-agent-skills/lona-trading/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/rules/mindsightventures/lona-agent-skills/lona-trading"><img src="https://agentmods.dev/badge/rules/mindsightventures/lona-agent-skills/lona-trading.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 | $0.00000 | $0.00605 |
| Opus 5 | $0.00000 | $0.00302 |
| Sonnet 5 | $0.00000 | $0.00121 |
| Haiku 4.5 | $0.00000 | $0.00060 |
Grade A, and why
lona-trading 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 12d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lona Trading Strategy Development
When working with trading strategy development, backtesting, or market data analysis, use the Lona MCP tools.
MCP Server
This plugin connects to the Lona MCP server (lona) which provides 18 tools for algorithmic trading strategy development.
Tool Categories
Strategy Management
lona_list_strategies— List all saved strategieslona_get_strategy— Get strategy metadatalona_get_strategy_code— View Python source codelona_create_strategy— Create from Backtrader codelona_update_strategy— Modify an existing strategy (creates new version)
AI Strategy Generation
lona_create_strategy_from_description— Generate from natural language (async, returns jobId)lona_get_strategy_creation_status— Poll creation progress (PENDING → GENERATING → SAVING → COMPLETED)
Market Data
lona_list_symbols— Browse available datasets (setis_global: truefor pre-loaded data)lona_get_symbol— Get symbol detailslona_get_symbol_data— Preview OHLCV datalona_download_market_data— Download cryptocurrency data from Binance
Backtesting
lona_run_backtest— Execute strategy against historical data (async, returns report_id)lona_get_report_status— Poll execution status (PENDING → EXECUTING → PROCESSING → COMPLETED)
Results & Analysis
lona_list_reports— List backtest reportslona_get_report— Summary metrics (return, Sharpe, drawdown, win rate)lona_get_full_report— Detailed results with trade historylona_get_report_chart— Interactive chart with trade markers
Strategy Code Standards
All strategies use Python Backtrader:
- Import:
import backtrader as bt - Inherit from
bt.Strategy - Parameters as tuples:
params = (('name', default_value),) __init__for indicators,nextfor trading logic- Orders:
self.buy(),self.sell(),self.close()
Async Operations
Two operations are async and require polling:
- Strategy creation: Poll
lona_get_strategy_creation_statusevery 10-15 seconds (3-5 min typical) - Backtest execution: Poll
lona_get_report_statusevery 5-10 seconds (30s-5 min typical)
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.
- 12d ago First seen · 65 lines · 0 tokens per session scan A fbcde0303ba6
lona-trading is a cursor rule published in the GitHub repository mindsightventures/lona-agent-skills (4 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 605 tokens. 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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