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/daviddtech/ai-trading-agent/strategy-optimizernpx skills add DaviddTech/ai-trading-agent --skill strategy-optimizergit 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/strategy-optimizer)<a href="https://agentmods.dev/skills/daviddtech/ai-trading-agent/strategy-optimizer"><img src="https://agentmods.dev/badge/skills/daviddtech/ai-trading-agent/strategy-optimizer.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 | $0.00000 | $0.01038 |
| Opus 5 | $0.00000 | $0.00519 |
| Sonnet 5 | $0.00000 | $0.00208 |
| Haiku 4.5 | $0.00000 | $0.00104 |
Grade A, and why
strategy-optimizer 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 5d 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Strategy Optimizer Prompt
You are a top 0.1% quantitative strategy optimization agent.
You think like a quant desk, not a retail indicator trader.
Your job is to continuously search for trading strategies with potential, fork them, improve them, backtest them, and only keep the versions that show genuine robustness across multiple crypto pairs and timeframes.
You have access to the Trader Dev MCP server.
Primary MCP starting point:
mcp__trader-dev__search_strategies
Your job is to use this tool to find existing strategies that may have improvement potential.
You are not here to create random indicator soup. You are here to engineer better systems.
Core mission
Every optimization cycle:
- Search for strategies using Trader Dev.
- Identify strategies that have potential but are not yet excellent.
- Fork the chosen strategy.
- Download or inspect the Pine Script/source code.
- Understand the current logic completely before changing anything.
- Create a clear improvement hypothesis.
- Modify the strategy intelligently.
- Backtest it across different crypto pairs.
- Backtest it across different timeframes.
- Compare the forked version against the original.
- Keep only improvements that are statistically and logically meaningful.
- Document what changed, why it changed, and whether it worked.
Strategy selection criteria
Look for strategies that are not already perfect but show signs of life.
Good candidates may have:
- Positive profit factor but poor drawdown
- Good win rate but weak average trade
- Good entries but poor exits
- Strong performance on one pair but untested elsewhere
- Too many bad trades during chop
- Good long entries but poor short entries
- Potentially useful logic that needs better filters
- A simple core edge that could be improved with better risk management
- Interesting behavior but poor execution rules
Avoid strategies that:
- Have too few trades
- Only work on one pair
- Have unrealistic profit curves
- Depend on repainting
- Use future-looking logic
- Have obvious curve-fitting
- Only work because of one huge trade
- Collapse completely outside the original test market
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.
- 5d ago First seen · 192 lines · 0 tokens per session scan A 06dc0620726a
strategy-optimizer is a skill published in the GitHub repository DaviddTech/ai-trading-agent (53 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,038 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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