loop-research

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Original

English
🇨🇳

Translation

Chinese

loop-research — a loop-graph preset for evidence-led choices

loop-research — 用于证据驱动决策的loop-graph预设

A thin authoring entry. It binds a research-and-selection pack, starts the owner interview, then follows
loop-graph
to compile the normal executor, ledger, directives, ops, and supervisor artifacts. It is not a research node, a second runtime, or a second template set.
这是一个轻量创作入口。它绑定研究与选择包,启动负责人访谈,随后遵循
loop-graph
编译标准执行器、台账、指令、运维和监管工件。它不是研究节点、第二运行时或第二模板集。

Fit check

适配检查

  • Use this when the approach is undecided and a decision needs comparative evidence from open-source projects, primary research, and a controlled benchmark or A/B experiment.
  • Use
    ../loop-deliver/SKILL.md
    once the approach is chosen, or
    ../loop-converge/SKILL.md
    for code consolidation.
  • For a short answer, one source lookup, or non-comparative literature summary, use the host's ordinary research task instead of a graph.
  • 当方案尚未确定,且决策需要来自开源项目、原创研究、对照基准测试或A/B实验的对比证据时,使用此技能。
  • 若方案已选定,请使用
    ../loop-deliver/SKILL.md
    ;若需代码整合,请使用
    ../loop-converge/SKILL.md
  • 对于简短回答、单来源查找或非对比类文献综述,请使用宿主的常规研究任务,而非图流程。

On invoke

调用时执行步骤

  1. Inspect the workspace, existing evidence, experiment harnesses, data policy, and current host the same way loop-graph does. Never ask which client this is when context already identifies it.
  2. Read and bind
    preset.md
    . That pack is the North Star, supervisor requirement, interview, evidence shape, method guards, knob overrides, and artifact emphasis. Do not redesign them.
  3. Start the owner interview immediately. Ask only the pack's unresolved choices — decision/scope, evidence budget and data authority, and launch — as recommended A/B (or A/B/C) choices. Do not ask the owner to invent evaluation criteria.
  4. Read and follow
    ../loop-graph/SKILL.md
    from When called from a preset skill through generate and deliver. Compile only from loop-graph's
    templates/
    . This skill never executes the generated nodes.
  1. 按照与loop-graph相同的方式检查工作区、现有证据、实验框架、数据策略和当前宿主。当上下文已明确客户身份时,请勿询问相关信息。
  2. 读取并绑定
    preset.md
    。该包涵盖北极星准则、监管要求、访谈大纲、证据规范、方法约束、参数覆盖规则和工件重点要求。请勿重新设计这些内容。
  3. 立即启动负责人访谈。仅询问包中未解决的选择项——决策/范围、证据预算与数据权限,以及启动方式——并提供推荐的A/B(或A/B/C)选项。请勿要求负责人自行制定评估标准。
  4. 读取
    ../loop-graph/SKILL.md
    并遵循其中从预设Skill调用时章节起至生成与交付环节的要求。仅使用loop-graph的
    templates/
    目录进行编译。本Skill不会执行生成的节点。