backtest

A command that combines several market factors into one signal and tests the portfolios it would create. A quintile backtest sorts assets into five groups by signal strength and compares their results.

In plain words
What is it for?
Use it to fit factor weights on training data, evaluate them on separate test data, and report long-short returns, turnover, and portfolio behavior.
Why use it?
It shows whether a group of individually promising factors works as a portfolio after trading costs, rather than relying only on single-factor scores.

Command

Install

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.

agentmods
npx agentmods add commands/minihellboy/factorminer/backtest
Clone the repo
git clone --depth 1 https://github.com/minihellboy/factorminer
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 94 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00012 $0.00094
Opus 5 $0.00006 $0.00047
Sonnet 5 $0.00002 $0.00019
Haiku 4.5 $0.00001 $0.00009

Measured yesterday against content hash b33275023f81, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

backtest 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.

integrations/factor-researcher/plugin/commands/backtest.md · 10 lines

What it actually says

Load the factor-backtest skill. Combine the library into a composite signal and quintile-backtest the implied portfolio under transaction costs. Fit weights on train, score on test. Report long-short return net of turnover costs as the headline.

Changes

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.

  1. yesterday First seen · 10 lines · 12 tokens per session scan A b33275023f81

Subscribe to this mod's changes

backtest is a command published in the GitHub repository minihellboy/factorminer (105 stars, last pushed 15d ago), licensed MIT. It adds 12 tokens to every session and 94 once invoked, about $0.0001 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.