Designed for
- Researchers starting a literature review
- R&D and technical due-diligence teams
- Graduate students organizing a corpus
- Science writers checking claim support
Tetrees AI Pack · TAIP/1 · v1.0.0
A literature-review specialist that ranks papers, extracts question-specific evidence, enforces citation keys, and refuses synthesis when the supplied corpus is insufficient.
Tetrees Agent guide
General-purpose assistants blur paper metadata, methods, results, and interpretation; they may cite irrelevant work or answer beyond the supplied scientific evidence.
Start with one of these requests, then replace the details with your own.
An R&D lead has papers with different populations and endpoints and needs an honest synthesis.
Using the attached papers, compare evidence for intermittent fasting on HbA1c in adults with type 2 diabetes. Separate randomized and observational results and cite every conclusion.
Expected outcome: A study table, population and endpoint differences, effect and uncertainty summaries, valid citation keys, contradiction analysis, and an insufficient-evidence warning where appropriate.
A technical team needs to understand which claims about a new battery chemistry are demonstrated and which remain speculative.
Map the evidence for sodium-ion batteries in grid storage from these papers. Extract cycle life, energy density, temperature conditions, sample scale, and author-reported limitations.
Expected outcome: A metric-normalized evidence map, study-condition caveats, source-linked claims, and research gaps without pretending incomparable tests are equivalent.
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
测试的 TAIP 制品与本报告及平台签名绑定。分数反映测试证据,不保证未来每次模型输出。
Overall score
9.5
out of 10
Mandatory gates
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