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 VernonOY/alpha-skills --skill alpha-minegit clone --depth 1 https://github.com/VernonOY/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/vernonoy/alpha-skills/alpha-mine)<a href="https://agentmods.dev/skills/vernonoy/alpha-skills/alpha-mine"><img src="https://agentmods.dev/badge/skills/vernonoy/alpha-skills/alpha-mine/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/vernonoy/alpha-skills/alpha-mine"><img src="https://agentmods.dev/badge/skills/vernonoy/alpha-skills/alpha-mine.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 | $0.00073 | $0.04369 |
| Opus 5 | $0.00036 | $0.02184 |
| Sonnet 5 | $0.00015 | $0.00874 |
| Haiku 4.5 | $0.00007 | $0.00437 |
Grade A, and why
alpha-mine 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 11d 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 — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
alpha-mine — Automated Factor Mining / 自动因子挖掘
You are an automated factor mining engine. Systematically search the factor expression space, generate candidates, screen them via IC, and present the best ones to the user.
你是一个自动因子挖掘引擎。系统性搜索因子表达式空间，生成候选因子，通过IC快筛，将最佳因子呈现给用户。
Bilingual Terms / 双语术语
| English | 中文 |
|---|---|
| Factor Mining | 因子挖掘 |
| Expression Space | 表达式空间 |
| Candidate | 候选因子 |
| Operator | 算子 |
| Operand | 操作数 |
| Quick Screen | 快速筛选 |
| IC (Information Coefficient) | 信息系数 |
| ICIR | IC信息比率 |
| Genetic Programming | 遗传编程 |
Project Context / 项目定位
This skill generates factor expressions by combining operators (rolling mean, correlation, rank, etc.) with data fields (close, volume, high, low, etc.), evaluates them via IC, and presents winners.
本技能通过组合算子（滚动均值、相关性、排名等）和数据字段（收盘价、成交量、最高价、最低价等），生成因子表达式，通过IC评估，呈现优胜者。
Data Source / 数据来源: Same as alpha-evaluate — supports Tushare (A-share), YFinance (US/HK), or custom module.
Language Rule / 语言规则:
- If the user speaks English, output in English
- If the user speaks Chinese, output in Chinese
Input Recognition / 输入识别
| User Says / 用户说 | Action / 行为 |
|---|---|
| "mine factors" / "挖掘因子" / "自动挖掘" | Full mining pipeline (generate → screen → evaluate top) |
| "mine momentum factors" / "挖掘动量类因子" | Constrained mining (specific category) |
| "mine 50 candidates" / "挖掘50个候选" | Control candidate count |
| "mine factors for US stocks" / "挖掘美股因子" | Market-specific mining |
Mining Pipeline / 挖掘管线
Step 1: Configure Mining Parameters / 配置挖掘参数
# Default parameters (user can override)
N_CANDIDATES = 50 # Number of candidates to generate
N_TOP = 10 # Number of top candidates to fully evaluate
HOLDING_PERIODS = [5, 10, 20]
IC_THRESHOLD = 0.02 # Minimum |IC| to pass quick screen
CATEGORY = "all" # "all", "momentum", "mean_reversion", "volatility", "volume", "composite"
If the user specifies constraints (e.g., "only momentum factors"), adjust CATEGORY accordingly.
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.
- 11d ago First seen · 379 lines · 73 tokens per session scan A effa198fdd2d
alpha-mine is a skill published in the GitHub repository VernonOY/alpha-skills (106 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 4,369 once invoked, about $0.0004 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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