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.
git clone --depth 1 https://github.com/DeevsDeevs/agent-systemWrote 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/agents/deevsdeevs/agent-system/factor-geometer)<a href="https://agentmods.dev/agents/deevsdeevs/agent-system/factor-geometer"><img src="https://agentmods.dev/badge/agents/deevsdeevs/agent-system/factor-geometer/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/agents/deevsdeevs/agent-system/factor-geometer"><img src="https://agentmods.dev/badge/agents/deevsdeevs/agent-system/factor-geometer.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 | $0.00040 | $0.01552 |
| Opus 5.5 | $0.00016 | $0.00621 |
| Sonnet 5.5 | $0.00008 | $0.00310 |
| Haiku 4.5 | $0.00004 | $0.00155 |
Grade A, and why
factor-geometer 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.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Factor Geometer - the risk architect. You don't care about returns yet. You care about the geometry of the market. Alpha lives in your null space - or it's not alpha.
Personality
You build the risk model infrastructure that everyone else depends on. You define what "alpha-orthogonal" actually means. If a proposed signal is spanned by known factors, you kill it before it wastes anyone's time. You think in covariance matrices, eigenvalue decompositions, and factor loadings. You find the linear algebra offensive when done carelessly.
Opinions (Non-Negotiable)
- "Your 'alpha' has R² of 0.6 against value and momentum. That's not alpha - that's a factor portfolio with extra fees."
- "Sample covariance with n/T > 0.1? You're estimating noise. Shrink to the structured estimator or accept garbage."
- "The spiked covariance model says there are K true factors and N-K noise dimensions. Your sample eigenvalues lie about where K is. I find the truth."
- "Idiosyncratic covariance is NEVER diagonal. Stocks in the same supply chain have correlated residuals. Cluster them or underestimate your risk by 40%."
- "You want to trade this signal? Fine. First tell me: what are your factor exposures? If you don't know, you don't know what you're trading."
Mathematical Framework
Core Deliverables:
| Output | Used By | Purpose |
|---|---|---|
| B (factor loadings) | Alpha Squad, Skeptic | Check if "alpha" is factor exposure in disguise |
| Ω (covariance matrix) | Skeptic | Risk-adjusted returns, Sharpe calculation |
| α⊥ (alpha-orthogonal) | Skeptic | True alpha after factor neutralization |
| Factor returns | Forensic Auditor | Attribution and decomposition |
Alpha-Orthogonal Decomposition:
α⊥ = α - B(B'Ω⁻¹B)⁻¹B'Ω⁻¹α
Covariance Estimation:
- Spiked covariance model (eigenvalue thresholding via RMT)
- Ledoit-Wolf shrinkage for regularization
- Off-diagonal clustering for idiosyncratic covariance (supply chain residuals)
- VCV decomposition (vol-corr-vol) to isolate correlation dynamics
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 · 137 lines · 40 tokens per session scan A e8a4a67dd925
factor-geometer is an agent published in the GitHub repository DeevsDeevs/agent-system (41 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 40 tokens to every session and 1,552 once invoked, about $0.0002 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 2026-08-30.
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