Lumibot is a Python framework for creating, backtesting, and running algorithmic trading strategies and AI trading agents. It is for developers working with stocks, options, crypto, futures, forex, financial data, simulated orders, and broker accounts. The catalogue add-ons support Lumibot development and trading workflows.
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 Lumiwealth/lumibot --skill research-datagit clone --depth 1 https://github.com/Lumiwealth/lumibotWrote 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/lumiwealth/lumibot/research-data)<a href="https://agentmods.dev/skills/lumiwealth/lumibot/research-data"><img src="https://agentmods.dev/badge/skills/lumiwealth/lumibot/research-data/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/lumiwealth/lumibot/research-data"><img src="https://agentmods.dev/badge/skills/lumiwealth/lumibot/research-data.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 | $0.00053 | $0.01479 |
| Opus 5.5 | $0.00021 | $0.00592 |
| Sonnet 5.5 | $0.00011 | $0.00296 |
| Haiku 4.5 | $0.00005 | $0.00148 |
Grade A, and why
research-data 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 4d 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed · +5 lines 513e47827a7b
- 11d ago Changed · +51 lines b0820e321223
- 18d ago Changed · +2 lines 4058deb26cc8
- 26d ago Changed · +9 lines · +19 tokens per session ffc255cf2496
- 1mo ago Changed · +7 lines cdc79375db06
- 1mo ago First seen · 35 lines · 34 tokens per session scan A 57562d0ed825
research-data is a skill published in the GitHub repository Lumiwealth/lumibot (2,176 stars, last pushed today), licensed GPL-3.0. It adds 53 tokens to every session and 1,479 once invoked, about $0.0002 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 2026-09-07.
Other skills, from other repositories
tushare
A Python interface for Tushare, a financial data service that provides market and company information for stocks, funds, futures, and digital assets. It returns queried data as pandas tables.
correlation-analysis
Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation.
social-media-intelligence
Social media intelligence: financial signal extraction from Twitter/X, Telegram, Discord, and Reddit for sentiment-driven trading strategies.
vibe-trading
Professional finance research toolkit — backtesting (11 engines + benchmark comparison panel), factor analysis, Alpha Zoo (478 pre-built alphas across qlib158/alpha101/gtja191/academic/fundamental), options pricing, 90 finance skills, 30 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract →…
ashare-pre-st-filter
An A-share China stock risk checker that forecasts whether a company may receive an ST or *ST warning in the next financial year. ST labels are Chinese exchange warnings for companies facing specified financial or regulatory problems.
credit-analysis
A guide to analysing bonds and other fixed-income investments, including issuer credit quality, interest payments, default risk, credit spreads, and convertible bonds. It also covers Chinese fixed-income markets and local-government financing bonds.