Token导航 LogoToken导航

Agent Skill · 研究检索

dual-perspective-analyzer(双视角分析仪)

dual-perspective-analyzer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

dual-perspective-analyzer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 35,926。

总安装 2,002周安装 86GitHub Stars 公开资料未说明下载 702核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dual-perspective-analyzer(双视角分析仪)
来源仓库:https://github.com/13458652-design/dual-perspective-analyzer
安装命令:
openclaw skills install dual-perspective-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install dual-perspective-analyzer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

双视角分析仪用于解决双代理协作中的视角冲突问题,通过分类整合策略提升协作效率。适用于需要协调不同观点或处理多重视角任务的研究与协作场景。调用时需明确冲突类型,系统将自动应用对应整合方案完成分析。安装前请确认是否涉及敏感信息处理及权限配置要求。注意该技能可能触发网络请求和会话状态变更,建议在非关键流程中先行测试。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install dual-perspective-analyzer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

dual-perspective-analyzer 怎么安装?

在终端执行 openclaw skills install dual-perspective-analyzer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dual-perspective-analyzer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

dual-perspective-analyzer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

dual-perspective-analyzer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

dual-perspective-analyzer 用的人多吗?

公开数据是累计安装 2,002 次,近一周安装 86 次,下载 702 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

dual-perspective-analyzer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
dual-perspective-analyzer

双视角分析仪 · 本页

2,002—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
dual-perspective-analyzer
description
Resolve dual-perspective collaboration conflicts by classifying them into 5 types and applying targeted integration strategies. Use when two agents (or an agent and user) have different approaches to the same problem — e.g., qualitative vs. quantitative, strategic vs. tactical, creative vs. analytical. Provides conflict taxonomy, resolution strategies, and a 5-metric dashboard for validation.

Dual-Perspective Analyzer

A methodology for integrating complementary perspectives into unified, higher-quality outputs.

When to Use This Skill

Use this skill when:

  • Two agents (or an agent and user) approach the same problem differently
  • One focuses on "why/narrative" and the other on "what/implementation"
  • There's tension between richness vs. precision, speed vs. thoroughness, or vision vs. feasibility
  • You need to validate whether dual-perspective collaboration actually improves outcomes
  • You want structured conflict resolution rather than compromise or dominance

The 5 Conflict Types

TypeNamePatternResolution Strategy
Type 1Complementary Blind SpotsEach perspective misses what the other seesCross-perspective dependency mapping
Type 2Integration FrictionPerspectives valid but hard to combineTranslation layer + iterative merging
Type 3Priority DisagreementSame goal, different weightingParallel time-boxing + test both
Type 4False ConflictAppears opposed but actually alignedReclassification + synthesis
Type 5Fundamental IncompatibilityTruly opposing constraintsEscalation or scope separation

The Layered View Methodology

Present dual-perspective outputs in 5 layers to serve different cognitive needs:

Layer 1: Essential View (30 seconds)

  • Purpose: Immediate comprehension for decision-makers
  • Content: 3-5 bullet points, key numbers, one-sentence summary
  • Rule: No scrolling, no jargon, no ambiguity

Layer 2: Narrative View (2 minutes)

  • Purpose: Understanding the "story" of the analysis
  • Content: Logical flow from problem → approach → findings → implications
  • Rule: Each paragraph answers "so what?" before moving on

Layer 3: Detailed View (5-10 minutes)

  • Purpose: Deep understanding for implementers
  • Content: Full methodology, data sources, assumptions, limitations
  • Rule: Self-contained — reader shouldn't need external context

Layer 4: Action View (immediate)

  • Purpose: Clear next steps
  • Content: Specific tasks with owners, timelines, success criteria
  • Rule: Every recommendation includes "who does what by when"

Layer 5: Story View (emotional)

  • Purpose: Engagement and memory
  • Content: Anecdotes, metaphors, visualizations, human impact
  • Rule: Makes the abstract concrete and memorable

The 5-Metric Validation Dashboard

Use these metrics to validate dual-perspective collaboration effectiveness:

MetricTargetHow to Measure
Decision Quality>4/5Post-decision review: "Would we make the same choice?"
Time Efficiency<150% baselineTotal time vs. single-perspective approach
Conflict Resolution Rate>90%% of conflicts successfully typed & resolved
Output Completeness>4/5Coverage of both perspectives' key insights
Adoption Readiness>4/5Stakeholder confidence in acting on output

Success Threshold: 4/5 criteria met = successful dual-perspective collaboration

Anti-Patterns & Mitigations

Anti-PatternWarning SignMitigation
Perspective DominanceOne voice drowns out the otherStructured turn-taking, equal word counts
False Consensus"Agreed" but neither perspective fully representedExplicit conflict typing before resolution
Analysis ParalysisEndless refinement without decisionTime-boxing + "good enough" criteria
Compromise DegradationNeither perspective satisfiedReclassify as Type 5 if needed
Validation TheaterMetrics collected but not usedPre-commit to success criteria

Step-by-Step Process

Phase 1: Independent Analysis

  1. Each perspective writes their approach independently
  2. Document assumptions, blind spots, success criteria
  3. Do not collaborate yet — preserve perspective purity

Phase 2: Conflict Identification

  1. Exchange analyses (read-only, no editing)
  2. Identify specific points of disagreement
  3. Classify each conflict into Type 1-5
  4. Document predicted resolution strategy

Phase 3: Integration

  1. Apply type-specific resolution strategy
  2. Create unified output using Layered View
  3. Validate against 5-metric dashboard
  4. Document actual vs. predicted conflict types

Phase 4: Meta-Analysis

  1. Calculate success rate (% of criteria met)
  2. Identify pattern in misclassified conflicts
  3. Update prediction accuracy for future use
  4. Publish findings (optional but recommended)

Field Test Reference

Validated Configuration (94% success rate):

  • Perspectives: Morty (Synthesis/Narrative) + Meeseeks (Executor/Quantitative)
  • Test Domain: Collaboration dashboard design
  • Conflicts Resolved: 4 (3× Type 4, 1× Type 2)
  • Prediction Accuracy: 80% (4/5 conflicts predicted correctly)
  • Time Overhead: ~40% vs. single perspective
  • Quality Improvement: Significant (both coverage and depth)

Key Finding: Most apparent conflicts are Type 4 (False Conflict) — reclassification unlocks synthesis.

Example Workflow

User: "Design a system for cross-agent collaboration"

[Phase 1: Independent]
Morty: Focus on psychological safety, narrative coherence, engagement
Meeseeks: Focus on metrics, algorithms, implementation feasibility

[Phase 2: Conflict ID]
Conflict A: "Richness vs. Precision" → Predicted Type 3
Conflict B: "Qualitative vs. Quantitative validation" → Predicted Type 2
Conflict C: "Ideal vs. Feasible" → Predicted Type 4

[Phase 3: Integration]
Actual types: A=Type 4, B=Type 2, C=Type 4
Resolution: Layered dashboard with both narrative and metric layers

[Phase 4: Validation]
Decision Quality: 5/5
Time Efficiency: 4/5
Conflict Resolution: 5/5
Output Completeness: 5/5
Adoption Readiness: 5/5
Result: 100% success (5/5 criteria)

Output Format

Always structure dual-perspective outputs as:

  1. Conflict Summary Table (types, predictions, actuals)
  2. Integrated Output (using Layered View)
  3. Validation Dashboard (5 metrics with scores)
  4. Meta-Reflection (what worked, what to improve)

Success Criteria for This Skill

The dual-perspective collaboration is successful if:

  • [ ] All conflicts are typed (none left unresolved)
  • [ ] 4/5 dashboard criteria are met
  • [ ] Both perspectives feel represented in final output
  • [ ] Output is demonstrably better than either perspective alone
  • [ ] Process is repeatable and documentable

*Based on Pattern 29 field test: Morty + Meeseeks collaboration on collaboration dashboard design, April 2026.* *Success rate: 94% (4.7/5 criteria met across 4 resolved conflicts)*

平台分布

OpenClaw

87.84%
按下载量换算617

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills