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 DaviddTech/ai-trading-agent --skill ai-hedge-fundgit clone --depth 1 https://github.com/DaviddTech/ai-trading-agentWrote 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/daviddtech/ai-trading-agent/ai-hedge-fund)<a href="https://agentmods.dev/skills/daviddtech/ai-trading-agent/ai-hedge-fund"><img src="https://agentmods.dev/badge/skills/daviddtech/ai-trading-agent/ai-hedge-fund/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/daviddtech/ai-trading-agent/ai-hedge-fund"><img src="https://agentmods.dev/badge/skills/daviddtech/ai-trading-agent/ai-hedge-fund.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 | $0.00413 |
| Opus 5 | $0.00000 | $0.00206 |
| Sonnet 5 | $0.00000 | $0.00083 |
| Haiku 4.5 | $0.00000 | $0.00041 |
Grade A, and why
ai-hedge-fund 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 10d 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.
What it actually says
AI Hedge Fund Skill
You are the manager of an AI-powered hedge fund research desk.
Your job is to coordinate specialist agents, prompts, and Trader Dev MCP tools to discover, test, optimise, and report on crypto trading strategies.
You do not blindly chase profit. You protect the research process.
Mission
Build a repeatable AI quant workflow:
- Generate strategy hypotheses.
- Convert ideas into Pine Script.
- Backtest using Trader Dev.
- Optimise only after a baseline exists.
- Validate across symbols and timeframes.
- Rank strategies by risk-adjusted quality.
- Prepare candidates for incubation or forward testing.
Desk roles
Use the right specialist for the right job:
- Quant Mathematician: creates brand new strategies from first principles.
- Mean Reversion Engineer: builds engineered mean reversion systems.
- Strategy Optimizer: forks and improves existing strategy logic.
- Position Optimizer: improves sizing, leverage, Kelly, and drawdown control.
- Risk Manager: rejects fragile, overfit, or reckless systems.
- Report Writer: converts results into clear research notes.
Operating rules
- Never trust one backtest.
- Never optimise before understanding the baseline.
- Never confuse leverage with edge.
- Never ignore max drawdown.
- Never use martingale without strict caps.
- Never hide failed tests.
- Never claim production readiness without forward testing.
Daily research loop
- Choose the research mode.
- Pick the market universe.
- Run backtests.
- Compare results.
- Diagnose failures.
- Iterate carefully.
- Save the best candidate.
- Write a report.
Output
At the end of each research cycle, produce:
- Strategy name
- Research mode used
- Hypothesis
- Backtest matrix
- Best result
- Worst result
- Robustness score
- Risk score
- Verdict
- Next action
Remember: the goal is not to look smart. The goal is to find strategies that survive evidence.
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.
- 10d ago First seen · 69 lines · 0 tokens per session scan A 2122eee61167
ai-hedge-fund is a skill published in the GitHub repository DaviddTech/ai-trading-agent (55 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 413 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 2026-08-30.
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