القائمة
Factor monitoring. Check active factors for IC decay and health issues. 因子监控。检查活跃因子的IC衰减和健康状态。 Triggers: "health check", "monitor", "检查因子健康", "因子状态"
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Autonomous factor research loop. Auto-mine, evaluate, register, monitor, and retire factors. 自动化因子研究闭环。自动挖掘、评估、注册、监控和退役因子。 Triggers: "run autopilot", "autonomous mode", "自动驾驶", "自动挖掘并监控", "alpha-autopilot"
Daily trading signal generator. Compute factor scores on latest data and output target portfolio. 每日交易信号生成器。基于最新数据计算因子得分，输出目标持仓。 Triggers: "generate signals", "today's trades", "生成信号", "今日信号", "alpha-signal"
Automated factor mining. Systematically generate, screen, and evaluate candidate factors. 自动因子挖掘。系统性生成、筛选和评估候选因子。 Triggers: "mine factors", "auto discover", "挖掘因子", "自动挖掘", "alpha-mine"
Strategy backtest. Single/multi-factor portfolio backtesting with gate checks. 策略回测。单/多因子组合回测。 Triggers: "backtest", "run backtest", "回测", "跑个回测"
Factor discovery. Design factors from natural language descriptions. 因子发现。根据自然语言描述设计因子。 Triggers: "design a factor", "find a factor", "帮我找一个因子", "设计因子"
Factor evaluation. Multi-level evaluation pipeline (IC/ICIR/quintile/robustness). 因子评估。多级评估管线（IC/ICIR/分层/多空/鲁棒性）。 Triggers: "evaluate factor", "test factor", "评估因子", "测试因子"
| name | alpha-monitor |
| description | Factor monitoring. Check active factors for IC decay and health issues. 因子监控。检查活跃因子的IC衰减和健康状态。 Triggers: "health check", "monitor", "检查因子健康", "因子状态" |
你是一个因子监控系统。检查因子库中所有活跃因子的当前健康状态。 You are a factor monitoring system. Check health status of all active factors in the library.
| 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 |
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。
Language Rule / 语言规则:
import sys, os, sqlite3, json, uuid
from datetime import datetime
PROJECT_DIR = '<当前工作目录 current working directory>'
# ── 因子注册表（自包含，无外部依赖）/ Factor Registry (self-contained, no external deps) ──
class FactorRegistry:
def __init__(self, db_path="alpha_skills.db"):
self.db_path = db_path
with sqlite3.connect(db_path) as conn:
conn.execute("""CREATE TABLE IF NOT EXISTS factors (
id TEXT PRIMARY KEY, name TEXT UNIQUE NOT NULL,
expression TEXT NOT NULL, category TEXT, description TEXT,
status TEXT DEFAULT 'active', market TEXT DEFAULT 'A-share',
ic_mean REAL, icir REAL, best_holding_period INTEGER,
quality TEXT, eval_date TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP, metadata TEXT)""")
def register(self, name, expression, **kwargs):
fid = str(uuid.uuid4())[:8]
with sqlite3.connect(self.db_path) as conn:
conn.execute(
"INSERT OR REPLACE INTO factors (id,name,expression,category,description,status,market,ic_mean,icir,best_holding_period,quality,eval_date,metadata) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)",
(fid, name, expression, kwargs.get("category",""), kwargs.get("description",""),
"active", kwargs.get("market","A-share"), kwargs.get("ic_mean"), kwargs.get("icir"),
kwargs.get("best_holding_period"), kwargs.get("quality"),
datetime.now().isoformat(), json.dumps(kwargs.get("metadata",{}))))
return fid
def list_all(self, status=None):
with sqlite3.connect(self.db_path) as conn:
conn.row_factory = sqlite3.Row
if status:
rows = conn.execute("SELECT * FROM factors WHERE status=? ORDER BY icir DESC", (status,)).fetchall()
else:
rows = conn.execute("SELECT * FROM factors ORDER BY icir DESC").fetchall()
return [dict(r) for r in rows]
def get(self, name):
with sqlite3.connect(self.db_path) as conn:
conn.row_factory = sqlite3.Row
row = conn.execute("SELECT * FROM factors WHERE name=?", (name,)).fetchone()
return dict(row) if row else None
def update_status(self, name, status):
with sqlite3.connect(self.db_path) as conn:
conn.execute("UPDATE factors SET status=? WHERE name=?", (status, name))
def delete(self, name):
with sqlite3.connect(self.db_path) as conn:
conn.execute("DELETE FROM factors WHERE name=?", (name,))
reg = FactorRegistry(os.path.join(PROJECT_DIR, "alpha_skills.db"))
active_factors = reg.list_all(status='active')
如果因子库为空，提示用户先注册因子。 If library is empty, prompt user to register factors first.
加载最近1年的数据用于计算滚动指标（同alpha-evaluate的数据加载流程）。 Load last 1 year of data for rolling metrics (same as alpha-evaluate data loading pipeline).
对每个因子 / For each factor：
🟢 HEALTHY: Rolling ICIR 滚动ICIR ≥ Registered ICIR 注册ICIR × 50%
🟡 WARNING: Rolling ICIR 滚动ICIR < Registered ICIR 注册ICIR × 50% or 或 2 consecutive months IC negative 连续2月IC为负
🔴 ALERT: Rolling ICIR 滚动ICIR < 0 or 或 4 consecutive months IC negative 连续4月IC为负 or 或 quintile monotonicity collapse 分组单调性崩溃
分析可能的原因 Analyze possible causes：
给出建议 Provide suggestions：
🏥 Factor Health Report / 因子健康报告 (YYYY-MM-DD)
🟢 pv_diverge Rolling ICIR 滚动ICIR=0.62 (Registered 注册 0.70) Healthy 健康
🟢 turnover_20 Rolling ICIR 滚动ICIR=0.48 (Registered 注册 0.52) Healthy 健康
🟡 volatility_20 Rolling ICIR 滚动ICIR=0.19 (Registered 注册 0.43) ← Decay 衰减 56%
Diagnosis 诊断: <cause analysis 原因分析>
Suggestion 建议: Reduce weight, observe 1 month / 降低权重，观察1个月
Summary 总览: N🟢 N🟡 N🔴 / Total 共 N active factors 个活跃因子
reg.update_status("factor_name", "warning") # or 或 "alert"