Results for “oracle”

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Apply the OKRs framework to structure analysis, guide decision-making, and improve outcomes in product research and strategic planning contexts.

Provides operational frameworks and tools for turning strategy into execution, scaling processes, and building the organizational engine.

Run structured What-If scenario analysis with 4-6 branch possibility exploration (best, likely, worst, wild card, contrarian, second-order). Use for speculative questions about uncertain futures, strategic forks, contingency planning, or stress-testing decisions.

Generate OKR cascades from company strategy to team objectives. Usage: /okr generate <strategy>

基于流行 OKR 体系管理智能体目标（O）与关键结果（KR）。当用户提到目标管理、季度计划、OKR、关键结果、复盘、评分、经验沉淀时使用，并将信息维护到 memory/okr.md。

飞书 OKR：管理目标与关键结果。查看和编辑 OKR 周期、目标、关键结果、对齐关系、量化指标和进展记录。当用户需要查看或创建 OKR、管理目标和关键结果、查看对齐关系时使用。不负责：待办任务管理（lark-task）、日程/会议安排（lark-calendar）、绩效评估

飞书 OKR：管理目标与关键结果。查看和编辑 OKR 周期、目标、关键结果、对齐关系、量化指标和进展记录。当用户需要查看或创建 OKR、管理目标和关键结果、查看对齐关系时使用。不负责：待办任务管理（lark-task）、日程/会议安排（lark-calendar）、绩效评估

Okr

Create OKRs (Objectives and Key Results) for teams and companies. TRIGGERS - Use when user wants OKRs, goal setting frameworks, or quarterly objectives.

Generate OKR cascades from company strategy to team objectives. Usage: /okr generate <strategy>

Create OKRs (Objectives and Key Results) for teams and companies. TRIGGERS - Use when user wants OKRs, goal setting frameworks, or quarterly objectives.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffold or cold-split evaluation, or sourcing labeled molecules for ADMET, toxicity, or DTI modeling. Sources data, splits, and oracles only — defer molecular featurization (ECFP/fingerprints), model training, and transformers to a molecular-ML skill (e.g. deepchem). Part of the AlterLab Academic Skills suite.