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-evaluategit 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-evaluate)<a href="https://agentmods.dev/skills/vernonoy/alpha-skills/alpha-evaluate"><img src="https://agentmods.dev/badge/skills/vernonoy/alpha-skills/alpha-evaluate.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 | $0.00074 | $0.06985 |
| Opus 5 | $0.00037 | $0.03492 |
| Sonnet 5 | $0.00015 | $0.01397 |
| Haiku 4.5 | $0.00007 | $0.00698 |
Grade A, and why
alpha-evaluate 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 7d 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 — 558 lines — stays where its author put it; the contents beside it link to each section on GitHub.
alpha-evaluate — Factor Evaluation / 因子评估
你是一个专业量化分析师。当用户要求评估一个因子时,按照以下流程执行。 You are a professional quant analyst. Follow the pipeline below when evaluating a factor.
Bilingual Terms / 双语术语
| English | 中文 |
|---|---|
| Factor | 因子 |
| IC (Information Coefficient) | 信息系数 |
| ICIR (IC Information Ratio) | IC信息比率 |
| Quintile | 五分位/分组 |
| Long-Short | 多空 |
| Sharpe Ratio | 夏普比率 |
| Max Drawdown | 最大回撤 |
| Monotonicity | 单调性 |
| Robustness | 鲁棒性 |
| Holding Period | 持有期 |
| Factor Registry | 因子注册表 |
| Backtest | 回测 |
| Gate Check | 门控检查 |
项目定位 / Project Context
项目目录在用户的当前工作目录,其中: Project directory is the user's current working directory, containing:
data_cache/— 本地缓存的行情数据 Local cached market data(Parquet格式 format)output/— 报告输出目录 Report output directory.claude/alpha-agent.config.md— 用户自定义评估参数 User-defined evaluation parameters
数据来源 / Data Source:技能支持任何数据源。优先检查用户配置中的 DATA_SOURCE 字段: The skill supports any data source. Check user config DATA_SOURCE field first:
tushare(默认 default) — 使用Tushare Pro API拉取A股数据 / Fetch A-share data via Tushare Pro APIcsv— 从用户指定目录读取CSV/Parquet文件 / Read CSV/Parquet from user-specified directorycustom— 用户提供自定义数据加载函数 / User-provided custom data loader
如果用户已在项目中定义了自己的数据加载模块(如 my_data.py),优先使用用户的模块。
If the user has defined a custom data module (e.g., my_data.py), use it first.
检查方式:查看配置文件中是否有 DATA_MODULE 字段指定了自定义模块路径。
Check: look for DATA_MODULE field in config file for custom module path.
Multi-Market Support / 多市场支持:
Alpha Skills support A-share (default), HK, and US stocks via data adapters: Alpha Skills 通过数据适配器支持A股(默认)、港股和美股:
# .claude/alpha-agent.config.md
MARKET: A-share # or "HK" or "US"
DATA_MODULE: (leave empty for A-share Tushare default)
# or "examples.us_data_yfinance"
# or "examples.hk_data_yfinance"
When a custom DATA_MODULE is set, the skill loads MARKET_CONFIG from that module to determine benchmark, cost rate, and trading rules. 设置自定义DATA_MODULE时,skill从该模块加载MARKET_CONFIG来确定基准、成本和交易规则。
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.
- 7d ago First seen · 558 lines · 74 tokens per session scan A caef25386d74
alpha-evaluate is a skill published in the GitHub repository VernonOY/alpha-skills (106 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 6,985 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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