---

name: alpha-gpt description: "Route AlphaGPT data ingestion, factor mining, live strategy, and dashboard workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

AlphaGPT

Use this repo skill for the AlphaGPT crypto-quant system. It helps future agents work with the repository's four main workflows without reopening the source tree for basic navigation:

• data ingestion from Birdeye/DexScreener into Postgres/Timescale
• factor-token mining, StackVM formula execution, and training artifacts
• live strategy, risk, portfolio state, and Solana/Jupiter execution
• Streamlit dashboard monitoring and local fixture generation

Start here

1. Read references/repo-provenance.md when you need to check whether this skill still matches the current AlphaGPT checkout or before a refresh.
2. Read references/install-and-operations.md for the public install baseline, dependency pin note, environment expectations, and safe import check.
3. Read references/troubleshooting.md for cross-cutting import, dependency, credential, DB, and live-operation failures.
4. Read references/experiments-and-exclusions.md for optional research scripts and explicit exclusions.
5. Run scripts/alpha_gpt_env_check.py when you want an offline, no-network preflight across env vars, files, and imports.

Route map

• data-pipeline: OHLCV ingestion, provider config, DDL preview, and safe preflight checks.
• factor-mining: feature engineering, formula grammar, StackVM execution, backtest scoring, and training artifacts.
• live-strategy: strategy runner, portfolio state, risk controls, and guarded Solana/Jupiter execution.
• dashboard-ops: Streamlit dashboard, read-only state inspection, and local fixture generation.

Public baseline

• Install from the repository root with python -m pip install -r requirements.txt.
• The source tree is not packaged as a pyproject.toml/setup.py distribution, so use the checkout itself as the import root when validating a local clone.
• If execution.trader fails on the newest Solana wheel because TokenAccountOpts is missing, consult the live-strategy troubleshooting notes for the verified solana==0.36.12 and websockets==15.0.1 compatibility pin.
• Core runtime facts were verified from the current source: source import roots are data_pipeline, model_core, execution, strategy_manager, and dashboard.

Minimal import check

From a checkout that is on PYTHONPATH or otherwise visible to the environment, a safe smoke check is:

python -I -c "import data_pipeline, model_core, execution, strategy_manager, dashboard"

If you need a deeper no-network preflight, use the bundled env checker instead of touching databases, RPC endpoints, or wallets.

What this skill does not do automatically

• It does not start the live strategy runner.
• It does not fetch Birdeye data or write Postgres rows as a default check.
• It does not submit Solana transactions.
• It does not launch Streamlit for you.
• It does not install optional research dependencies from requirements-optional.txt unless you explicitly choose the optional research workflows.

Safe reading order for common tasks

• "Why is no market data showing up?" -> data-pipeline troubleshooting.
• "How do I inspect or validate a formula?" -> factor-mining references and smoke script.
• "How do I configure the bot safely?" -> live-strategy reference and offline config checker.
• "Why is the dashboard empty?" -> dashboard-ops reference and fixture generator.

Notes for later refreshes

• Read references/repo-provenance.md and compare the current checkout before deciding whether to refresh this skill.
• If the repository adds package metadata, new workflows, or additional service/backends, route those through a refresh rather than widening the existing instructions silently.