Skip to content
store
backtesting-frameworks

Self-hosted alternatives to backtesting-frameworks

5 self-hosted AI Skills apps to use instead, best rated first.

Top picks

  1. C

    claude-to-deerflow

    Launch

    claude-to-deerflow is an agent skill that lets an assistant send messages and questions to a running DeerFlow instance through its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code

    Self-hosted

  2. O

    open-notebook

    Launch

    open-notebook is an agent skill for organising research with Open Notebook, a self-hosted alternative to NotebookLM. It arranges sources, notes and AI conversations into research notebooks. Sources can be PDFs, web pages, audio, video and O

    Self-hosted

  3. R

    Reactive Resume

    Launch

    Reactive Resume is a free and open-source resume builder for writing resumes and cover letters, checking the work, and tracking job applications. You create a free account, import an existing resume or start from scratch, and see the finish

    Open sourceSelf-hosted

  4. S

    self-hosted-funnel-launch

    Launch

    Self-hosted funnel launch is an agent skill that takes a funnel from an empty install to published on infrastructure you control, using the Autonnel funnel builder, which is licensed Apache-2.0. The result covers a landing page, checkout, a

    Self-hosted

  5. G

    get-convex/convex-backend

    Launch

    Convex is an open-source reactive database for web app developers. It combines a database, a place to write server functions in pure TypeScript, and client libraries that keep the app's data live, so screens update as the data changes. Beca

    Self-hosted

About backtesting-frameworks

B

backtesting-frameworks

Robust backtesting systems

backtesting-frameworks is an agent skill from the wshobson/agents collection for building backtesting systems for trading strategies. Its goal is to produce reliable performance estimates by avoiding the common errors that make backtests look better than they are. The skill names look-ahead bias, survivorship bias and overfitting, and covers realistic modeling of transaction costs, slippage and commissions. It describes event-driven and vectorized backtester implementations, so an agent can pick the style that fits the strategy, and it covers walk-forward optimization and Monte Carlo simulation to test how robust a strategy is. The skill is meant for developing trading strategy backtests, building backtesting infrastructure, validating performance, comparing strategy alternatives and implementing walk-forward analysis. It is a software guide, not investment advice: it does not recommend a strategy, and a backtest does not guarantee future results. The skill is installed with the skills CLI from the wshobson/agents repository. Its skills.sh page showed about 16.3K installs and passing results from three security audits at the time of the scan.

View backtesting-frameworksAll AI Skills apps
Price
Free
Made by
wshobson
Category
AI Skills
Website
github.com/wshobson/agents/backtesting-frameworks