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/aaaaqwq/agi-super-team/backtesting-frameworksnpx skills add aAAaqwq/AGI-Super-Team --skill backtesting-frameworksgit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/aaaaqwq/agi-super-team/backtesting-frameworks)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/backtesting-frameworks"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/backtesting-frameworks.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 5.1 | $0.00036 | $0.00260 |
| Opus 5 | $0.00018 | $0.00130 |
| Sonnet 5 | $0.00007 | $0.00052 |
| Haiku 4.5 | $0.00004 | $0.00026 |
Grade A, and why
backtesting-frameworks 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 yesterday.
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
Backtesting Frameworks
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
Use this skill when
- Developing trading strategy backtests
- Building backtesting infrastructure
- Validating strategy performance and robustness
- Avoiding common backtesting biases
- Implementing walk-forward analysis
Do not use this skill when
- You need live trading execution or investment advice
- Historical data quality is unknown or incomplete
- The task is only a quick performance summary
Instructions
- Define hypothesis, universe, timeframe, and evaluation criteria.
- Build point-in-time data pipelines and realistic cost models.
- Implement event-driven simulation and execution logic.
- Use train/validation/test splits and walk-forward testing.
- If detailed examples are required, open
resources/implementation-playbook.md.
Safety
- Do not present backtests as guarantees of future performance.
- Avoid providing financial or investment advice.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 42 lines · 36 tokens per session scan A c53613fcde1f
backtesting-frameworks is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 260 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 2026-09-05.
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