Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mphinance/alpha-skillsnpx agentmods add skills/mphinance/alpha-skills/pair-trade-screenerWrote 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/pair-trade-screener)<a href="https://agentmods.dev/skills/mphinance/alpha-skills/pair-trade-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/pair-trade-screener/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/pair-trade-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/pair-trade-screener.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 | $0.00087 | $0.04598 |
| Opus 5.5 | $0.00035 | $0.01839 |
| Sonnet 5.5 | $0.00017 | $0.00920 |
| Haiku 4.5 | $0.00009 | $0.00460 |
Grade A, and why
pair-trade-screener 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.
This is a copy
86% identical to pair-trade-screener — 70 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 623 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pair Trade Screener
Overview
This skill identifies and analyzes statistical arbitrage opportunities through pair trading. Pair trading is a market-neutral strategy that profits from the relative price movements of two correlated securities, regardless of overall market direction. The skill uses rigorous statistical methods including correlation analysis and cointegration testing to find robust trading pairs.
Core Methodology:
- Identify pairs of stocks with high correlation and similar sector/industry exposure
- Test for cointegration (long-term statistical relationship)
- Calculate spread z-scores to identify mean-reversion opportunities
- Generate entry/exit signals based on statistical thresholds
- Provide position sizing for market-neutral exposure
Key Advantages:
- Market-neutral: Profits in up, down, or sideways markets
- Risk management: Limited exposure to broad market movements
- Statistical foundation: Data-driven, not discretionary
- Diversification: Uncorrelated to traditional long-only strategies
When to Use This Skill
Use this skill when:
- User asks for "pair trading opportunities"
- User wants "market-neutral strategies"
- User requests "statistical arbitrage screening"
- User asks "which stocks move together?"
- User wants to hedge sector exposure
- User requests mean-reversion trade ideas
- User asks about relative value trading
Example user requests:
- "Find pair trading opportunities in the tech sector"
- "Which stocks are cointegrated?"
- "Screen for statistical arbitrage opportunities"
- "Find mean-reversion pairs"
- "What are good market-neutral trades right now?"
Analysis Workflow
Step 1: Define Pair Universe
Objective: Establish the pool of stocks to analyze for pair relationships.
Option A: Sector-Based Screening (Recommended)
Select a specific sector to screen:
- Technology
- Financials
- Healthcare
- Consumer Discretionary
- Industrials
- Energy
- Materials
- Consumer Staples
- Utilities
- Real Estate
- Communication Services
What ships with it
5 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.
- 1mo ago First seen · 623 lines · 87 tokens per session scan A f79ba78e8714
pair-trade-screener is a skill published in the GitHub repository mphinance/alpha-skills (28 stars, last pushed 10d ago), licensed MIT. It adds 87 tokens to every session and 4,598 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to pair-trade-screener, differing in 70 lines, and is treated as a copy.
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