Python

Frameworks for comparing the A-share, H-share and US ADR prices of one Chinese company: AH premium, arbitrage signals, dual-listing valuation and delisting risk.

HKUDS/Vibe-Trading

Pulls free market data from the AKShare Python library: A-share, US and Hong Kong prices, futures, China macro series and forex, with notes on symbol formats and Chinese column names.

HKUDS/Vibe-Trading

Detects 15 classic candlestick patterns with vectorized pandas code and combines bullish and bearish scores into a long, short or flat trading signal.

HKUDS/Vibe-Trading

Fetches public crypto market data (candles, tickers, order books, trades) from 100+ exchanges through CCXT, and serves as the fallback when OKX is unavailable.

HKUDS/Vibe-Trading

Builds event-driven analysis for A-share companies: merger arbitrage spreads, shareholder buying and selling signals, equity incentives, placements and ST or delisting warnings; Chinese text.

HKUDS/Vibe-Trading

Scores news, announcements and macro events with the LLM, stores them in an event CSV and blends the decaying event signal with technical signals in signal_engine.py.

HKUDS/Vibe-Trading

Adds realistic execution assumptions to backtests: fixed, linear and square-root slippage, delayed fills, VWAP and TWAP logic and market-impact cost estimates; never for live orders.

HKUDS/Vibe-Trading

Evaluates mutual funds, private funds and ETFs by return, risk and risk-adjusted metrics, style box and drift, and manager quality, then builds FOF portfolios; Chinese text.

HKUDS/Vibe-Trading

Builds value or growth stock screens from PE, PB, ROE and financial statement fields for backtests, using tushare data for A-shares and yfinance for Hong Kong and US stocks.

HKUDS/Vibe-Trading

Generates trading signals from the Ichimoku five-line system using Tenkan and Kijun crossovers, cloud position and cloud direction, implemented in pandas.

HKUDS/Vibe-Trading

Fetches minute candlesticks from OKX, Tushare or yfinance, computes intraday VWAP, TWAP and volume distribution, and runs minute-level backtests by setting an interval in config.json.

HKUDS/Vibe-Trading

Trains scikit-learn models with walk-forward validation on features from OHLCV data to predict return direction and turn the predictions into trading signals.

HKUDS/Vibe-Trading

Pulls A-share price data from 通达信 (TDX) servers through the mootdx library over TCP, free and without an API key, as a stable fallback when akshare scraping is throttled.

HKUDS/Vibe-Trading

Ranks stocks by standardized factor scores (momentum, reversal, volatility, volume and valuation) and builds an equal-weight TopN portfolio with periodic rebalancing.

HKUDS/Vibe-Trading

Trades mean reversion between two correlated instruments using the Z-score of their price ratio, going long one leg and short the other when the ratio stretches.

HKUDS/Vibe-Trading

Explains why a portfolio beat or lagged its benchmark with Brinson sector attribution, factor alpha and beta decomposition, timing evaluation and benchmark comparison.

HKUDS/Vibe-Trading

Translates a Python backtest strategy or a plain description into Pine Script v6, TDX formulas and MQL5 code for TradingView, Chinese broker terminals and MetaTrader 5.

HKUDS/Vibe-Trading

Guides your agent through unit-root, cointegration, GARCH, bootstrap and regression-diagnostic tests on financial time series, using a tested helper module.

HKUDS/Vibe-Trading

Measures portfolio and backtest risk with VaR, CVaR, maximum drawdown, Monte Carlo simulation, tail modeling and stress tests, using one tested risk module.

HKUDS/Vibe-Trading

Reads crypto market liquidity from stablecoin supply changes, USDT and USDC mint and burn events, exchange reserves and velocity, to time capital rotation.

HKUDS/Vibe-Trading

Takes a trading idea from request to backtest: pins down instruments and dates, writes config.json and a signal engine, runs the backtest and iterates on the metrics.

HKUDS/Vibe-Trading

Expert guidance on the Google Agent Development Kit (ADK) for Python.

cnemri/google-genai-skills

Abrir y operar el companion visual de Selina para elegir una direccion de estilo en proyectos con interfaz.

686f6c61/alfred-dev

Kitaru test layout, CI workflows, and release-workflow behavior.

zenml-io/kitaru

Calculates value-added tax from a tax-inclusive sales amount, VAT rate and input tax using a calculator tool, with risk checks and filing suggestions.

Serein-81/financial_rag

Onboard a repository to use Offload for parallel test execution on Modal.

imbue-ai/offload

Reads, inspects, and writes Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO.

K-Dense-AI/scientific-agent-skills

Analyzes flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces.

K-Dense-AI/scientific-agent-skills

Plans, configures, inspects, restarts, and analyzes bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks.

K-Dense-AI/scientific-agent-skills

Supports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation.

K-Dense-AI/scientific-agent-skills

Builds, registers, debugs, and operates bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP.

K-Dense-AI/scientific-agent-skills

Local document and PDF parsing that returns spatial text with bounding boxes.

K-Dense-AI/scientific-agent-skills

Inspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs.

K-Dense-AI/scientific-agent-skills

Authors, reviews, migrates, simulates, and troubleshoots official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots.

K-Dense-AI/scientific-agent-skills

Supports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference.

K-Dense-AI/scientific-agent-skills

Performs bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage…

K-Dense-AI/scientific-agent-skills

Analyzes, validates, converts, and transforms materials structures and computed materials data with pymatgen.

K-Dense-AI/scientific-agent-skills

Builds, inspects, tests, and analyzes bounded process-based discrete-event simulations with SimPy.

K-Dense-AI/scientific-agent-skills

Best practices for writing Blender Python add-ons using the bpy API, covering operators, panels, properties, registration, and API-safe scripting.

Mindrally/skills

World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics.

alirezarezvani/claude-skills

Measure GEO visibility from an approved, file-backed engine observation bundle.

yaojingang/GEOHub

Panel data analysis with Python using linearmodels and pandas.

meleantonio/awesome-econ-ai-stuff

TRIGGER when user asks to add a Python-backed function endpoint to an existing Python-backed microservice.

microbus-io/fabric

Python asyncio 및 async/await 패턴 가이드. An agent skill from jh941213/my-cc-harness.

jh941213/my-cc-harness

A skill your agent uses when adding e2a email capabilities to an application or codebase: outbound sending, inbound signed webhooks, REST polling, or SDK integration.

tokencanopy/e2a

Best practices for the Common utilities package in LlamaFarm.

llama-farm/llamafarm

A skill your agent uses whenever a pull request is opened, reopened, or synchronized in microsoft/apm to assess whether and how the documentation corpus must change to stay truthful with the…

microsoft/apm

A skill your agent uses when writing, fixing, editing, or refactoring Python tests.

ertugrul-dmr/clean-code-skills