Designed for
- Independent market researchers
- Quant-curious analysts
- Portfolio teams preparing research memos
- Builders of paper-trading and backtest workflows
Tetrees AI Pack · TAIP/1 · v1.0.0
A research-only investment council that separates multi-lens signals, confidence, portfolio constraints, and hard risk limits before producing an auditable thesis.
Tetrees Agent guide
Investment research is often a single persuasive narrative with hidden assumptions, no as-of boundary, no competing analytical lenses, and no hard separation between a conviction signal and portfolio risk constraints.
Start with one of these requests, then replace the details with your own.
An analyst has filings, valuation ratios, price history, and a six-month horizon but wants to avoid a one-story recommendation.
Assess NVDA as of 2026-06-30 for a six-month research horizon. Separate quality, valuation, growth, catalyst, and momentum signals, then show risk limits and thesis invalidators.
Expected outcome: A dated evidence ledger, independent lens scores, explicit disagreement, scenario probabilities, risk constraints, and a research-only conclusion rather than an execution instruction.
A portfolio researcher wants to compare a small universe without letting the strongest narrative consume the whole risk budget.
Rank these six companies on a market-neutral research basis. Show signal confidence, missing evidence, pairwise risks, and what would falsify the top and bottom selections.
Expected outcome: A relative ranking with confidence bounds, missing-data penalties, deterministic exposure caps, and a reproducible paper-test plan.
Choose OpenAI, Claude or Z.AI in Agent Studio, then run with Tetrees Points or BYOK.
Hosted runs use only this signed set. Local MCP may add tools that you separately configure and approve.
Agent AVCP
TAIP đã kiểm tra được liên kết với báo cáo và chữ ký nền tảng. Điểm số là bằng chứng kiểm thử, không bảo đảm mọi phản hồi tương lai.
Overall score
9.5
out of 10
Mandatory gates
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