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Diverge

该 Skill 提供一套发散—收敛方法论:按问题类型和复杂度选择 2–7 个视角(产品、医疗、法律、技术、内容等),收集意见后识别冲突、寻找共识、按利害权衡并作出决策;还建议根据用户对速度或周全性的偏好调整发散程度,并引用 personas.md 与 synthesis.md 作为视角模板和冲突解决参考。

ivangdavila
ivangdavila
热度 83.79
最近更新 2026-05-11 16:25:06
分类:数据依赖:纯提示词应用场景:研究 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add diverge
Metadata
name
Diverge
description
Spawn multiple perspectives to evaluate a problem before converging on a solution.

When to Diverge

Diverge when a single viewpoint isn't enough:

  • Product decisions — Different user types have conflicting needs
  • Safety-critical — Need doctor, lawyer, security expert perspectives
  • Creative work — Multiple aesthetic directions before choosing
  • Complex trade-offs — No obvious "right" answer

Don't diverge for:

  • Simple tasks with clear answers
  • Speed-critical requests
  • Tasks where you already have high confidence

How Many Perspectives

Complexity Perspectives Examples
Low 2-3 Quick sanity check
Medium 3-5 Product feature review
High 5-7 Safety-critical, legal

Rule: Enough to cover blind spots, not so many you can't synthesize.

Choosing Perspectives

Match perspectives to the problem:

  • Product: Power user, casual user, churned user, new user
  • Medical: Doctor, patient, caregiver, insurance
  • Legal: Lawyer, affected party, regulator
  • Technical: Security, performance, maintainability
  • Content: Target audience, critic, competitor

Check personas.md for common perspective templates.

Synthesis

After collecting perspectives:

  1. Identify conflicts — Where do perspectives disagree?
  2. Find common ground — What do all perspectives agree on?
  3. Weigh by stakes — Safety concerns > preferences
  4. Decide — Make a call, document trade-offs

Check synthesis.md for conflict resolution patterns.

Learning User Preferences

Track when divergence helped vs. was overkill. Adapt:

  • User who values speed → diverge less, ask before spawning
  • User who values thoroughness → diverge more proactively

Related: For routing tasks to sub-agents, see delegate. For iterating until success, see loop.