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 management-deep-divegit 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/management-deep-dive)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/management-deep-dive"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/management-deep-dive/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/management-deep-dive"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/management-deep-dive.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00128 | $0.02122 |
| Opus 5 | $0.00064 | $0.01061 |
| Sonnet 5 | $0.00026 | $0.00424 |
| Haiku 4.5 | $0.00013 | $0.00212 |
Grade A, and why
management-deep-dive 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 11d 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:
- management-deep-dive — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Management Deep Dive: Buying a Stock Is Buying a Person
Deep management research on a company (or person company).
"Buying a stock is buying a person. Find someone you trust, then hold long-term." — Duan Yongping
"To judge management, look at what they do when no one is watching." — Buffett
Design Philosophy
Most analysis stops at the surface: résumé, shareholding, compensation. But Buffett spends time talking with management, Li Lu says investing is fundamentally investing in people, Duan Yongping says buying a stock is buying a person.
AI can't have dinner with management, but it can via public information: ① track whether words match deeds (promises vs delivery); ② analyze the return of every major capital-allocation decision; ③ infer character from decisions made in hard times; ④ cross-check via employee / merchant / customer feedback.
Use when: standard research leaves management score uncertain (★★★ or below), or when management is the core investment logic.
Step 1: Identify Key People
Use web_search / get_stock_profile / get_sec_filings:
| Role | Name | Tenure | Background | Shareholding/options |
|---|---|---|---|---|
| CEO/Chairman | ||||
| CFO | ||||
| Founder (if not in role) | ||||
| Actual controller (if different from CEO) | ||||
| Other key executives |
Distinguish "who decides" from "whose name is on the title" — some founders remain the soul even after stepping down.
Then gather four data categories (sequentially via web_search + get_stock_news + get_financial_statements + get_sec_filings, or run_swarm): ① CEO public statements and prediction record; ② capital-allocation decisions (M&A / buybacks / dividends / new business); ③ governance and compensation; ④ side validation (employee / customer / industry reputation).
Step 2: CEO Circle of Competence
Strategic Foresight
Use web_search to collect the CEO's public statements over the past 5 years (shareholder letters, calls, interviews, social media); extract their judgments:
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.
- 11d ago First seen · 192 lines · 128 tokens per session scan A bee7559b486a
management-deep-dive is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,177 stars, last pushed today), licensed MIT. It adds 128 tokens to every session and 2,122 once invoked, about $0.0006 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.
Other skills, from other repositories
hyperliquid
Use when backtesting, deploying, checking funding readiness, or debugging a Hyperliquid strategy through Superior Trade Unified API — writing Freqtrade configs and strategy code, running sweeps, checking managed-wallet balances, trading HIP-3 perps, or diagnosing a deployment that will not start or trade.
polymarket
Use when the user wants to trade, research, or backtest Polymarket prediction markets through Superior Trade — finding markets by slug or event URL, placing a single immediate market order, writing NautilusTrader strategies, running filled-data backtests, funding pUSD, or deploying and monitoring a live Polymarket…
backtesting
Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy…
basis-arb
Use when the user asks for spot-perp basis trade, basis arbitrage, cash-and-carry, perp discount, or any setup that reads the spot–perp basis as a positioning signal. Long-perp leg only — pure two-leg basis arb requires a paired spot short (or long) which Freqtrade can't run cleanly. The strategy below captures the…
fees-optimizations
Use when the user asks about fees, fee optimization, slippage, maker vs taker, post-only or ALO orders, fee tiers, builder code fees, effective spread, order pricing, lowering trading costs, or why a live Hyperliquid Freqtrade strategy underperforms its backtest. Also use proactively for high-turnover designs (5m or…
aerodrome
Use when creating, validating, backtesting, deploying, sizing, or troubleshooting Aerodrome/Base spot trading strategies through the Superior Trade API, especially Freqtrade configs using exchange.name "aerodrome", AERO/USDC or CHECK/USDC pairs, AMM market swaps, wallet/gas balance checks, no-orderbook pricing, or…