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Algo Setup

  • 15 installs
  • 7 repo stars
  • Updated April 28, 2026
  • marketcalls/openalgo-execution-skills

Helps with ai & agent building tasks.

About

algo-setup is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • algo-setup
  • AI & Agent Building
  • AI-coding skill

Algo Setup by the numbers

  • 15 all-time installs (skills.sh)
  • +3 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #11,187 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/marketcalls/openalgo-execution-skills --skill algo-setup

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Listed on Skillselion
Installs15
repo stars7
Last updatedApril 28, 2026
Repositorymarketcalls/openalgo-execution-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Set up the local Python environment for building and running OpenAlgo dual-mode trading strategies.

Arguments

$0 (optional) = python interpreter name (python, python3, python3.12). Default: python.

What to do

1. Detect the OS (Windows / macOS / Linux) via uname -s or os.name. Use OS-specific install commands for the TA-Lib C library (which pip install ta-lib depends on).

2. Create venv if not already present:

   python -m venv venv

3. Install TA-Lib C library (required by Python ta-lib):

  • macOS: brew install ta-lib
  • Ubuntu/Debian: sudo apt install libta-lib-dev (may need sudo apt update)
  • Windows: pip install ta-lib uses pre-built wheels - no C library install needed

4. Activate venv and install Python packages from requirements.txt:

   # Linux/macOS
   source venv/bin/activate
   pip install -r requirements.txt

   # Windows
   venv\Scripts\activate
   pip install -r requirements.txt

5. Scaffold folders:

   strategies/
       (empty - generated strategies will land here)
   backtests/
       (empty - generated backtest CSV/HTML output lands here)

6. Create `.env` by copying .env.sample and prompt the user to fill in OPENALGO_API_KEY:

   cp .env.sample .env

7. Verify the install by running:

   from openalgo import api, ta
   import vectorbt as vbt
   import talib
   import sklearn
   import xgboost
   print("OK")

8. Print next steps:

   Setup complete. Next:
     1. Edit .env and set OPENALGO_API_KEY
     2. Make sure OpenAlgo is running at http://127.0.0.1:5000
     3. Generate a strategy: /algo-strategy ema-crossover SBIN NSE 5m

Avoid

  • Do not use icons/emojis in output
  • Do not auto-run OPENALGO_API_KEY=... in the shell - the user pastes it into .env manually
  • Do not assume pip exists outside the venv after step 4 - always activate first

When the user already has a venv

Skip step 2. Activate the existing venv, run pip install -r requirements.txt against it, and continue.

Failure modes

  • TA-Lib install fails on Linux: tell the user to run sudo apt update && sudo apt install build-essential libta-lib-dev. If that fails (older distros), suggest skipping TA-Lib and using only INDICATOR_LIB="openalgo" in strategies.
  • OpenAlgo not running: setup completes but the verify-install step's from openalgo import api works (SDK installs without network). Real connection is verified in /algo-strategy.

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