Vibe-Trading is a personal trading agent that gives an AI system tools for market analysis, algorithmic trading, backtesting, and related workflows. It is for users who want an agent to research and evaluate trading strategies or manage simulated and other trading activities. The catalogue contains skills that expose these trading capabilities to compatible agents.
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 HKUDS/Vibe-Trading --skill deep-company-seriesgit clone --depth 1 https://github.com/HKUDS/Vibe-TradingWrote 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/hkuds/vibe-trading/deep-company-series)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/deep-company-series"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/deep-company-series/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/hkuds/vibe-trading/deep-company-series"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/deep-company-series.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00160 | $0.02411 |
| Opus 5 | $0.00080 | $0.01205 |
| Sonnet 5 | $0.00032 | $0.00482 |
| Haiku 4.5 | $0.00016 | $0.00241 |
Grade A, and why
deep-company-series 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- deep-company-series — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep-Company Series: An 8-Part Deep Dive on One Company
Write an 8-part deep-dive series (~120k words total) on a single company, from cognitive reset to a decision framework. The core IP is not "writing well" but "revising strictly" — most finance long-form violates this skill's fact-check standard.
1. When to Use
The user wants "textbook-level" deep research on a company, published as a series of long-form articles. Distinct from a single research report:
- 8 parts, ~120k words, full loop from cognitive reset to a decision framework
- Each part stands alone (shareable singly) but shares one valuation / management / price framework
- Written for readers willing to spend 90 minutes understanding one company
Not for: a single research report, earnings note, sector study — use other skills (fundamentals / earnings / sector).
2. Series Template (8 Parts)
| # | Title template | Core question | Words |
|---|---|---|---|
| 01 | You think you understand X — you don't | Cognitive reset: break 3 common illusions | 4,000-5,000 |
| 02 | X's moat — {one-line business essence} |
Is the moat deep; will it be there in 5/10 years | 6,000-8,000 |
| 03 | X's biggest profit engine — {most profitable business} |
What is the core business; why it persists | 6,000-8,000 |
| 04 | The other company hidden on X's balance sheet — {hidden asset} |
Investment portfolio / subsidiary / hidden value | 8,000-10,000 |
| 05 | In the AI (or current narrative) era, is X a winner or loser | Era variable: decompose the impact by business | 8,000-10,000 |
| 06 | Reading X's financials the Buffett way | Financial depth: gross margin / FCF / ROE / SBC | 8,000-10,000 |
| 07 | {management quote} — is X's management worth entrusting |
Capital-allocation discipline + integrity test + succession | 8,000-10,000 |
| 08 | At what price to buy, what signal to sell (finale) | DCF 3-scenario + red lines + position framework | 10,000-12,000 |
Plus 00-series-overview.md as an index (unpublished).
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.
- 13d ago First seen · 148 lines · 160 tokens per session scan A f6537516f279
deep-company-series is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,258 stars, last pushed today), licensed MIT. It adds 160 tokens to every session and 2,411 once invoked, about $0.0008 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 2026-08-30.
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