ZhuLinsen / alphasift
Full-market stock discovery for AI agents: A-shares plus US/HK/JP/KR/TW/IN, auditable YAML strategies, optional LLM ranking, sector-diversified picks, and true T+N evaluation vs. benchmark. AI选股
Why this job: says: benchmark
What it does
- Python API. from alphasift import screen, evaluate_saved_run, then screen("dual_low", use_llm=False, market="cn").
- LLM context. --context "..." adds market notes, and --candidate-context-file adds per-stock research.
- Post-analysis (L3). the local scorecard runs by default. --post-analyzer dsa sends the final shortlist to daily_stock_analysis for single-stock deep analysis.
- Hotspots. alphasift hotspots and alphasift hotspot "" rank A-share themes and resolve leader stocks with cache and fallback metadata.
- Agent and UI payloads. alphasift overview --json, alphasift serve, and alphasift doctor data-sources --all-strategies --explain. Endpoints are listed in the usage guide.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 5 days ago
- Stars
- 428
- +49 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 2
- Last 90 days
- Issues
- 89% closed
- 1 still open
- Pull requests
- 36 merged
- 2 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
Topics
- agent
- economics
- finance
- fintech
- llm
- python
- quant
- stock
- a-shares
- ai-agent
- multi-market
- quantitative-finance
Project record
- JobEvals and observability
- StatusListed
- Commits108
- Forks234
- Watching6
- Stars in 28 days+57
- CreatedApr 12, 2026
- First seen by usNov 7, 2026
- CheckedNov 9, 2026