Agent skill · research science · koreal6803
finlab
Comprehensive guide for FinLab quantitative trading package across global stock markets (TW, US, KR, JP, HK; both single-name equities and ETFs/funds). Use when working with trading strategies, backtesting, stock data, FinLabDataFrame, factor analysis, stock selection, or when the user mentions FinLab, trading, quant trading, US equity, S&P 500 / NASDAQ 100, SPY / QQQ, sector or leveraged ETFs, ETF rotation, 美股, or stock market analysis. Includes data access, strategy development, backtesting workflows, best practices, and US-market specifics (data availability map, filing-date-aligned quarterly fundamentals, US universe construction, USMarket vs. USFundMarket defaults, and ETF backtesting).
Why this skill is useful
Provides domain-specific knowledge and workflows for quantitative trading using the FinLab package that the AI wouldn't reliably generate on its own.
What it needs
Requires uv installed locally. Requires finlab account access. About 9k tokens when loaded. Last updated 2026-07-19. 407 stars on the source repository.
What this skill does
FinLab Quantitative Trading Package Prerequisites Before running any FinLab code, verify these in order: 1. uv is installed (Python package manager): If uv is not installed, tell the user to install it. After installing, ensure uv is on PATH: 2. FinLab is installed via uv (requires >= 2.0.0): Or use uv run for zero-setup execution (recommended for one-off scripts): uv run --with auto-creates a temporary environment with dependencies — no venv management needed. Prefer zero-install? Run notebooks directly in FinLab Studio — a hosted Jupyter environment with finlab preinstalled and your account already logged in. 3. Logged in to FinLab (finlab >= 2.0; no legacy API token required): Desktop (has a browser): log in once; credentials are cached locally: Headless / cron / Docker: on a machine with a browser, log in and run: Set all three exported variables — FINLABREFRESHTOKEN, FINLABSESSIONID, and FINLABAPIKEY — in the headless environment. FinLab uses them automatically. Treat the output as credentials: use your platform's secret storage and do not paste it into chat or commit it. Google Colab: run finlab.login() in a cell and follow the login link. Migrating from legacy tokens: FINLABAPITOKEN and finlab.login('<apitoken>') are deprecated. Run python -m finlab migrate, set up browser login or the three environment variables above, then remove the old token from your configuration. Legacy-token status: No removal version or date is publicly confirmed in the official authentication guide; the 2026/08/01 date in client warning text is not a removal announcement. Dropping the client-side fallback and rejecting legacy tokens server-side are separate changes, and a cached data.get() call does not test server authentication — use the supported login flow above. Language Respond in the user's language. If user writes in Chinese, respond in Chinese. If in English, respond in English. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills koreal6803/finlab--ea6a2b