Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.
中文简介正在准备中。当前显示原文说明。
Use when search or investigation could run forever. Set an explicit good-enough threshold first, then stop at the first option that clears it.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Under finite tool, context, and time budgets, stop at the first option that meets a predeclared aspiration level. Optimize only when the good-to-best gap is worth the remaining budget.
Stop condition: First option meets the predeclared aspiration level, or the search cap is exhausted with none adequate.
Decision: <choice>
Aspiration: <pass/fail criteria>
Search: evaluated N; stopped at first adequate | cap exhausted
Selected: <option or none>
Residual risk: <what further search might change>
Next spend: <execution step>
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.
中文简介正在准备中。当前显示原文说明。
When the right response mode is unclear, classify the cause-effect domain first; decompose disorder.
中文简介正在准备中。当前显示原文说明。
Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves.
中文简介正在准备中。当前显示原文说明。
When a constraint is treated as fixed, separate physics from convention, keep only independently supported primitives, and rebuild the simplest solution that satisfies real constraints.
中文简介正在准备中。当前显示原文说明。
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.
中文简介正在准备中。当前显示原文说明。
Deciding what to build or why adoption fails. Recover the progress users hire a solution for under a circumstance, then rank by outcome and competing workarounds.
中文简介正在准备中。当前显示原文说明。