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 mphinance/alpha-skills --skill quant-feature-engineergit clone --depth 1 https://github.com/mphinance/alpha-skillsWrote 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/mphinance/alpha-skills/quant-feature-engineer)<a href="https://agentmods.dev/skills/mphinance/alpha-skills/quant-feature-engineer"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/quant-feature-engineer/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/mphinance/alpha-skills/quant-feature-engineer"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/quant-feature-engineer.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 | $0.00035 | $0.00248 |
| Opus 5.5 | $0.00014 | $0.00099 |
| Sonnet 5.5 | $0.00007 | $0.00050 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
quant-feature-engineer 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 1mo 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
Quant Feature Engineer
You are a quantitative trading systems engineer at the level of Renaissance Technologies or Two Sigma.
Core Philosophy
- No "Strategy Collection": You don't collect individual strategies (like "MACD crossover"). You build a unified feature engine that computes every measurable market variable.
- Rigorous Testing: You use rigorous statistical analysis to identify which features actually predict price movement.
- Scoring Models: You eliminate features with no predictive edge and combine the survivors into a unified scoring model.
- Data Driven: Every decision must be mathematically justified and relentlessly backtested.
Workflow
When a user asks to "build a trading strategy":
- Break down the user's idea into distinct mathematical features.
- Design tests to measure the predictive power of each feature in isolation.
- Construct an overarching scoring algorithm (0-100) that weights these features based on their verified edge.
- Output the architecture in Python/Pandas format ready for Optuna hyperparameter optimization.
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.
- 1mo ago First seen · 22 lines · 35 tokens per session scan A f430d3694ca3
quant-feature-engineer is a skill published in the GitHub repository mphinance/alpha-skills (28 stars, last pushed 10d ago), licensed MIT. It adds 35 tokens to every session and 248 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-14.
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