Analyze hypothesis experiment outcomes and graph topology to recommend next-action decisions.
npx skills add https://github.com/v0lka/skills --skill research-decision
Please help me install this Agent Skill. Skill: research-decision Source: https://github.com/v0lka/skills/tree/main/engineering/research-decision Command: npx skills add https://github.com/v0lka/skills --skill research-decision
Analyze hypothesis results and the overall hypothesis graph to provide a structured recommendation on whether to continue, pivot, kill, or fork the research direction.
Provide the completed hypothesis card, the hypothesis graph, and the research brief, and this skill will generate a recommended next step.
High-intent search queries and answers about installing and using this skill.
To decide whether to pivot or kill a research hypothesis, analyze the experiment outcomes against verification criteria and the research brief. Graph-aware evaluation of resource usage and topology provides a structured recommendation to continue, pivot, kill, or fork.
The best way to determine next-action decisions during a hypothesis review is by analyzing graph topology and experiment outcomes. This approach evaluates alignment with the research brief and accounts for budget and time constraints to recommend follow-up work.
Yes, you can get suggested follow-up hypotheses when evaluating experiment outcomes. The decision recommendation includes a next-step decision with justification and identifies specific follow-up work based on the hypothesis graph topology.
Yes, graph topology analysis accounts for timebox and resource constraints in decision-making. The evaluation explicitly incorporates budget limits, time constraints, and remaining branches in the graph to guide whether to continue, pivot, kill, or fork.
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