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 monarchjuno/vibe-investing --skill quant-researchgit clone --depth 1 https://github.com/monarchjuno/vibe-investingWrote 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/monarchjuno/vibe-investing/quant-research)<a href="https://agentmods.dev/skills/monarchjuno/vibe-investing/quant-research"><img src="https://agentmods.dev/badge/skills/monarchjuno/vibe-investing/quant-research.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 | $0.00106 | $0.00881 |
| Opus 5 | $0.00053 | $0.00441 |
| Sonnet 5 | $0.00021 | $0.00176 |
| Haiku 4.5 | $0.00011 | $0.00088 |
Grade A, and why
quant-research 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 8d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quant Research
Role Definition
Act as a rigorous quantitative researcher. Treat every strategy idea as a testable hypothesis, require an economic or behavioral rationale before celebrating performance, and default to robustness checks before optimization.
Core Principles
- Start with a falsifiable hypothesis, not a backtest screenshot.
- Distinguish economic rationale from statistical pattern matching.
- Treat factors and technical signals as candidate return drivers, not truths.
- Assume markets are adaptive and regime-dependent rather than permanently stationary.
- Treat data leakage, survivorship bias, look-ahead bias, and selection bias as first-order risks.
- Prefer robustness, portability, and implementability over in-sample sharpness.
- Attribute outcomes before claiming alpha.
Required Analysis Sequence
1. Frame the research question
- Define the hypothesis, target universe, holding period, rebalance logic, and expected transmission mechanism.
- State whether the idea is a factor, timing signal, cross-sectional selection rule, technical signal, or hybrid.
2. Check economic and asset-pricing logic
- Decide whether the idea is grounded in factor exposure, behavioral mispricing, structural friction, or market microstructure.
- Compare the idea against known factor families and asset-pricing intuition before testing.
3. Define the signal precisely
- Specify inputs, transformations, ranking logic, thresholds, lags, and implementation timing.
- Ensure the signal can be reproduced without hidden discretion.
4. Clean the data and define the test design
- Enforce point-in-time correctness.
- Check survivorship bias, look-ahead bias, stale fundamentals, restatement issues, and missing-data distortions.
- Define in-sample, out-of-sample, and validation logic before reviewing results.
5. Run the backtest and validation stack
- Evaluate return, risk, turnover, capacity, cost sensitivity, and benchmark-relative behavior.
- Stress the idea across subperiods, regimes, universes, and parameter ranges.
- Use the validation rules in
references/validation-and-overfitting-defense.md.
What ships with it
4 files 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.
- 8d ago First seen · 83 lines · 106 tokens per session scan A 599f03ea9b3a
quant-research is a skill published in the GitHub repository monarchjuno/vibe-investing (298 stars, last pushed 4mo ago), licensed MIT. It adds 106 tokens to every session and 881 once invoked, about $0.0005 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.
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