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 agentmods add skills/hkuds/vibe-trading/execution-modelnpx skills add HKUDS/Vibe-Trading --skill execution-modelgit 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/execution-model)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/execution-model"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/execution-model.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.03229 |
| Opus 5 | $0.00020 | $0.01614 |
| Sonnet 5 | $0.00008 | $0.00646 |
| Haiku 4.5 | $0.00004 | $0.00323 |
Grade A, and why
execution-model 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.
How it starts
The opening of the file, as written. The whole thing — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Execution Modeling
Overview
Provide more realistic execution assumptions for backtests, including slippage models, market-impact estimation, and execution-algorithm principles. This skill is for backtest simulation only and does not involve live order execution.
Slippage Models
Why Slippage Models Are Needed
Idealized backtest: filled at the close, zero slippage
Real world:
1. The order book has a bid-ask spread
2. Large orders push prices (market impact)
3. Execution is delayed (there is latency from signal to fill)
No slippage model -> overly optimistic backtest -> losses in live trading
Do not retype these models. All four are implemented and tested in
src/quantlib/impact.py; import them. The tested versions validate their inputs —
a zero ADV raises instead of dividing by zero, and a negative delay_bars raises
instead of silently introducing look-ahead bias.
from src.quantlib.impact import fixed_slippage, linear_impact, sqrt_impact, delayed_execution
1. Fixed Slippage Model
fixed_slippage(price=100.0, direction=1, bps=5.0) # 100.05 (buy pays up)
fixed_slippage(price=100.0, direction=-1, bps=5.0) # 99.95 (sell receives less)
direction is 1 to buy or -1 to sell, and must be exactly one of those — it
multiplies the impact, so an unchecked 2 would silently double the modelled cost.
bps defaults to DEFAULT_SLIPPAGE_BPS (5.0).
Reference fixed-slippage assumptions by market:
| Market | Instrument | Suggested Slippage (bps) | Notes |
|---|---|---|---|
| China A-share large cap | CSI 300 constituents | 3-5 | Good liquidity |
| China A-share small cap | CSI 1000 constituents | 5-10 | Average liquidity |
| China micro-cap | market cap < 5 billion RMB | 10-30 | Poor liquidity |
| US large cap | AAPL / MSFT | 1-3 | Excellent liquidity |
| Hong Kong stocks | Hang Seng constituents | 5-10 | Less liquid than A / US |
| BTC spot | BTC-USDT | 2-5 | Good OKX liquidity |
| ETH spot | ETH-USDT | 3-8 | Slightly worse than BTC |
| Small altcoins | other -USDT pairs |
10-50 | Liquidity varies widely |
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 First seen · 336 lines · 41 tokens per session scan A da126eefad69
execution-model is a skill published in the GitHub repository HKUDS/Vibe-Trading (32,384 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 3,229 once invoked, about $0.0002 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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