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Agent Skill · 研究检索

synthesis-and-analogy(综合与类比)

synthesis-and-analogy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

synthesis-and-analogy 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 41,736。

总安装 1,148周安装 46GitHub Stars 公开资料未说明下载 372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

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:synthesis-and-analogy(综合与类比)
来源仓库:https://github.com/lyndonkl/claude
仓库路径:skills/synthesis-and-analogy
安装命令:
npx skills add lyndonkl/claude --skill "synthesis-and-analogy"
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 npx skills 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。

AgentSkills.tonpx skills
npx skills add lyndonkl/claude --skill "synthesis-and-analogy"

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。

synthesis-and-analogy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。适用于知识综合与类比推理的场景支持,可辅助跨领域问题解决。

通过 npx skills add 命令从 GitHub 安装,需确认宿主环境支持逻辑推理模块。安装前建议评估是否涉及复杂语义理解或外部知识库接入。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/synthesis-and-analogy

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add lyndonkl/claude --skill "synthesis-and-analogy";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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

synthesis-and-analogy 怎么安装?

在终端执行 npx skills add lyndonkl/claude --skill "synthesis-and-analogy"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

synthesis-and-analogy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

synthesis-and-analogy 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

synthesis-and-analogy 是免费的吗?

来源标注的许可证是 MIT。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。

synthesis-and-analogy 用的人多吗?

公开数据是累计安装 1,148 次,近一周安装 46 次,下载 372 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。

synthesis-and-analogy 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Codex,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。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 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
synthesis-and-analogy

综合与类比 · 本页

1,148—需要联网MIT未收录

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
synthesis-and-analogy
description
Use when synthesizing information from multiple sources (literature review, stakeholder feedback, research findings, data from different systems), creating or evaluating analogies for explanation or problem-solving (cross-domain transfer, "X is like Y", structural mapping), combining conflicting viewpoints into unified framework, identifying patterns across disparate sources, finding creative solutions by transferring principles from one domain to another, testing whether analogies hold (surface vs deep similarities), or when user mentions "synthesize", "combine sources", "analogy", "like", "similar to", "transfer from", "integrate findings", "what's it analogous to".

Synthesis & Analogy

Table of Contents

Purpose

Synthesize information from multiple sources into coherent insights and use analogical reasoning to transfer knowledge across domains, explain complex concepts, and find creative solutions.

When to Use

Information Synthesis:

  • Literature review (combine 10+ research papers into narrative)
  • Multi-source integration (customer feedback + analytics + competitive data)
  • Conflicting viewpoint reconciliation (synthesize disagreeing experts)
  • Pattern identification across sources (themes from interviews, support tickets, reviews)

Analogical Reasoning:

  • Explain complex concepts (use familiar domain to explain unfamiliar)
  • Cross-domain problem-solving (transfer solution from different field)
  • Creative ideation (find novel solutions through structural mapping)
  • Teaching/communication (make abstract concepts concrete)

Combined Synthesis + Analogy:

  • Synthesize multiple analogies to build richer understanding
  • Use analogies to reconcile conflicting sources ("both are right from different perspectives")
  • Transfer synthesized insights from one domain to another

What Is It

Synthesis: Combining information from multiple sources into unified, coherent whole that reveals patterns, resolves conflicts, and generates new insights beyond individual sources.

Analogy: Structural mapping between domains where relationships in source domain (familiar) illuminate relationships in target domain (unfamiliar). Good analogies preserve deep structure, not just surface features.

Example - Synthesis: Synthesizing 15 customer interviews + 5 surveys + support ticket analysis → "Customers struggle with onboarding (87% mention), specifically Step 3 configuration (65% abandon here), because terminology is domain-specific (42% request glossary). Three user types emerge: novices (need hand-holding), intermediates (need examples), experts (need speed)."

Example - Analogy: "Microservices architecture is like a city of specialized shops vs monolithic architecture like a department store. City: each shop (service) independent, can renovate without closing whole city, but must coordinate deliveries (APIs). Department store: everything under one roof (codebase), easier coordination, but renovating one section disrupts whole store. Trade-off: flexibility vs simplicity."

Workflow

Copy this checklist and track your progress:

Synthesis & Analogy Progress:
- [ ] Step 1: Clarify goal and gather sources/domains
- [ ] Step 2: Choose approach (synthesis, analogy, or both)
- [ ] Step 3: Apply synthesis or analogy techniques
- [ ] Step 4: Test quality and validity
- [ ] Step 5: Refine and deliver insights

Step 1: Clarify goal

For synthesis: What sources? What question are we answering? What conflicts need resolving? For analogy: What's source domain (familiar)? What's target domain (explaining)? What's goal (explain, solve, ideate)? See Common Patterns for typical goals.

Step 2: Choose approach

Synthesis only → Use Synthesis Techniques. Analogy only → Use Analogy Techniques. Both → Start with synthesis to find patterns, then use analogy to explain or transfer. For straightforward cases → Use resources/template.md. For complex multi-domain synthesis → Study resources/methodology.md.

Step 3: Apply techniques

For synthesis: Identify themes across sources, note agreements/disagreements, resolve conflicts via higher-level framework, extract patterns. For analogy: Map structure from source to target (what corresponds to what?), identify shared relationships (not surface features), test mapping validity. See Synthesis Techniques and Analogy Techniques.

Step 4: Test quality

Self-assess using resources/evaluators/rubric_synthesis_and_analogy.json. Synthesis checks: captures all sources? resolves conflicts? identifies patterns? adds insight? Analogy checks: structure preserved? deep not surface? limitations acknowledged? helps understanding? Minimum standard: Score ≥3.5 average.

Step 5: Refine and deliver

Create synthesis-and-analogy.md with: synthesis summary (themes, agreements, conflicts, patterns, new insights) OR analogy explanation (source domain, target domain, mapping table, what transfers, limitations), supporting evidence from sources, actionable implications.

Synthesis Techniques

Thematic Synthesis (identify recurring themes):

  1. Extract: Read each source, note key points and themes
  2. Code: Label similar ideas with same theme tag (e.g., "onboarding friction", "pricing confusion")
  3. Count: Track frequency (how many sources mention each theme?)
  4. Rank: Prioritize by frequency × importance
  5. Synthesize: Describe each major theme with supporting evidence from sources

Conflict Resolution Synthesis (reconcile disagreements):

  • Meta-level framework: Both right from different perspectives (e.g., "Source A prioritizes speed, Source B prioritizes quality - depends on context")
  • Scope distinction: Disagree on scope ("Source A: feature X broken for enterprise. Source B: works for SMB. Synthesis: works for SMB, broken for enterprise")
  • Temporal: Disagreement over time ("Source A: strategy X failed in 2010. Source B: works in 2024. Context changed: market maturity")
  • Null hypothesis: Genuinely conflicting evidence → state uncertainty, propose tests

Pattern Identification (find cross-cutting insights):

  • Look for repeated structures (same problem in different guises)
  • Find causal patterns (when X, then Y across multiple sources)
  • Identify outliers (sources that contradict pattern - why?)
  • Extract meta-insights (what does the pattern tell us?)

Example: Synthesizing 10 postmortems → Pattern: 80% of incidents involve config change + lack of rollback plan. Outliers: 2 incidents hardware failure. Meta-insight: Need config change review process + automatic rollback capability.

Analogy Techniques

Structural Mapping Theory:

  1. Identify source domain (familiar, well-understood)
  2. Identify target domain (unfamiliar, explaining)
  3. Map entities: What in source corresponds to what in target?
  4. Map relationships: Preserve relationships (if A→B in source, then A'→B' in target)
  5. Test mapping: Do relationships transfer? Are there unmapped elements?
  6. Acknowledge limits: Where does analogy break down?

Surface vs Deep Analogies:

  • Surface (weak): Share superficial features (both round, both red) - not illuminating
  • Deep (strong): Share structural relationships (both have hub-spoke topology, both use feedback loops) - insightful

Example - Surface: "Brain is like computer (both process information)" - too vague, doesn't help Example - Deep: "Brain neurons are like computer transistors: neurons fire/don't fire (binary), connect in networks, learning = strengthening connections (weights). BUT neurons are analog/probabilistic, computer precise/deterministic" - preserves structure, acknowledges limits

Analogy Quality Tests:

  • Systematicity: Do multiple relationships map (not just one)?
  • Structural preservation: Do causal relations transfer?
  • Productivity: Does analogy generate new predictions/insights?
  • Scope limits: Where does analogy break? (Always acknowledge)

Common Patterns

Pattern 1: Literature Review Synthesis

  • Goal: Combine research papers into narrative
  • Technique: Thematic synthesis (extract themes, note agreements/conflicts, identify gaps)
  • Output: "Research shows X (5 studies support), but Y remains controversial (3 for, 2 against due to methodology differences). Gap: no studies on Z population."

Pattern 2: Multi-Stakeholder Synthesis

  • Goal: Integrate feedback from design, engineering, product, customers
  • Technique: Conflict resolution synthesis (meta-level framework, scope distinctions)
  • Output: "Design wants A (aesthetics), Engineering wants B (performance), Product wants C (speed). All valid - prioritize C (speed) for v1, A (aesthetics) for v2, B (performance) as ongoing optimization."

Pattern 3: Explanatory Analogy

  • Goal: Explain technical concept to non-technical audience
  • Technique: Structural mapping from familiar domain
  • Output: "Git branches are like alternate timelines in sci-fi: main branch is prime timeline, feature branches are 'what if' explorations. Merge = timeline convergence. Conflicts = paradoxes to resolve."

Pattern 4: Cross-Domain Problem-Solving

  • Goal: Solve problem by transferring solution from different field
  • Technique: Identify structural similarity, map solution elements
  • Output: "Warehouse routing problem is structurally similar to ant colony optimization: ants find shortest paths via pheromone trails. Transfer: use reinforcement learning with 'digital pheromones' (successful route weights) to optimize warehouse paths."

Pattern 5: Creative Ideation via Analogy

  • Goal: Generate novel ideas by exploring analogies
  • Technique: Forced connections, random domain pairing, systematic variation
  • Output: "How is code review like restaurant food critique? Critic (reviewer) evaluates dish (code) on presentation (readability), taste (correctness), technique (architecture). Transfer: multi-criteria rubric for code review focusing on readability, correctness, architecture."

Guardrails

Synthesis Quality:

  • Covers all relevant sources (no cherry-picking)
  • Resolves conflicts explicitly (doesn't ignore disagreements)
  • Identifies patterns beyond what individual sources state (adds value)
  • Distinguishes facts from interpretations
  • Cites sources for claims
  • Acknowledges gaps and uncertainties

Analogy Quality:

  • Maps structure not surface features (deep analogy)
  • Explicitly states what corresponds to what (mapping table)
  • Tests validity (do relationships transfer?)
  • Acknowledges where analogy breaks down (limitations)
  • Doesn't overextend (knows when to stop pushing analogy)
  • Appropriate for audience (familiar source domain)

Avoid:

  • False synthesis: Forcing agreement where genuine conflict exists
  • Surface analogies: "Both are round" doesn't help understanding
  • Analogy as proof: Analogies illustrate, don't prove
  • Overgeneralization: One source ≠ pattern
  • Cherry-picking: Ignoring inconvenient sources
  • Mixing levels: Confusing data with interpretation

Quick Reference

Inputs Required:

For synthesis:

  • Multiple sources (papers, interviews, datasets, feedback, research)
  • Question to answer or goal to achieve
  • Conflicts or patterns to identify

For analogy:

  • Source domain (familiar, well-understood)
  • Target domain (unfamiliar, explaining or solving)
  • Goal (explain, solve problem, generate ideas)

Techniques to Use:

Synthesis:

  • Thematic synthesis → Identify recurring themes
  • Conflict resolution → Reconcile disagreements via meta-framework
  • Pattern identification → Find cross-cutting insights

Analogy:

  • Structural mapping → Map entities and relationships
  • Surface vs deep test → Ensure structural not superficial similarity
  • Validity test → Check if relationships transfer

Outputs Produced:

  • synthesis-and-analogy.md with:

- Synthesis: themes, agreements, conflicts resolved, patterns, new insights, supporting evidence - Analogy: source domain, target domain, mapping table (what↔what), transferred insights, limitations - Actionable implications

Resources:

Minimum Quality Standard:

  • Synthesis: covers all sources, resolves conflicts, identifies patterns, adds insight
  • Analogy: structural mapping clear, deep not surface, limitations acknowledged
  • Both: evidence-based, cited sources, actionable
  • Average rubric score ≥ 3.5/5 before delivering

平台分布

Claude Code

25.08%
按下载量换算93

Gemini CLI

21.68%
按下载量换算81

Antigravity

17.93%
按下载量换算67

windsurf

13.4%
按下载量换算50

OpenCode

7.95%
按下载量换算30

Cursor

3.13%
按下载量换算12

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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