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Agent Skill · 研究检索

media-meta-analysis(媒体元分析)

media-meta-analysis 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。

media-meta-analysis 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;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 22,538。

总安装 4,529周安装 185GitHub Stars 69下载 1,450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
unknown

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:media-meta-analysis(媒体元分析)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/media-meta-analysis
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill media-meta-analysis
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。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill media-meta-analysis

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。

media-meta-analysis 用于媒体相关研究的检索与筛选,支持多宿主环境中的信息聚合。适用于关键词驱动的内容查找、来源线索匹配和研究资料整理。通过 npx skills add 命令从 agent-skills 仓库安装使用。安装前应核实权限、维护状态及是否触发联网或文件访问。

建议查阅原始文档了解分析方法与适用范围。

来源仓库内路径:skills/media-meta-analysis

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 https://github.com/jwynia/agent-skills --skill media-meta-analysi…;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

media-meta-analysis 怎么安装?

在终端执行 npx skills add https://github.com/jwynia/agent-skills --skill media-meta-analysis。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

media-meta-analysis 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。

media-meta-analysis 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。

media-meta-analysis 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

media-meta-analysis 用的人多吗?

公开数据是累计安装 4,529 次,近一周安装 185 次,下载 1,450 次,GitHub 69 星。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。

media-meta-analysis 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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

  • 需要明确授权才能用到公司项目里的场景。
  • 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
media-meta-analysis

媒体元分析 · 本页

4,52969需要联网未明确通过

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

Media Meta-Analysis

Purpose

Synthesize patterns and connections across multiple individual media analyses to reveal deeper insights, conceptual networks, and emergent themes. Operates on collections of analyzed content, not individual pieces.

Core Principle

The whole reveals what the parts cannot. Patterns invisible in individual sources become visible across collections.


When to Use

Use after analyzing multiple pieces with individual extraction (e.g., media content extraction framework). This framework operates on collections of analyses, not raw media.


Collection Assessment

1. Corpus Composition

Document collection characteristics:

  • Content types: Video, article, podcast, etc.
  • Temporal distribution: Recency, historical coverage
  • Creator diversity: Single source or multiple
  • Topic distribution: Narrow or broad
  • Depth distribution: Quick takes vs. deep dives
  • Audience variations: Expert vs. general

Identify biases or gaps in coverage

2. Concept Frequency Analysis

AnalysisWhat to Track
Most frequent conceptsCore themes
High connection densityHub concepts
Isolated conceptsOrphan ideas
Concept clustersRelated idea groups
Terminology variationsSame idea, different words
Evolution over timeHow ideas develop

3. Argument Pattern Identification

Map the argumentation landscape:

  • Recurring claim types
  • Common evidence patterns
  • Shared assumptions across sources
  • Consistent logical structures
  • Frequent fallacies
  • Areas of consensus vs. contention

Connection Mapping

1. Concept Bridges

Discover connections between disparate sources:

  • Shared conceptual foundations
  • Complementary frameworks
  • Terminological equivalences
  • Parallel reasoning patterns
  • Similar metaphorical structures
  • Common historical/theoretical references

Map connection strength and directionality

2. Contradiction Detection

Identify meaningful tensions:

TypeExample
Direct claim contradictionsSource A says X, Source B says not-X
Competing interpretationsSame evidence, different conclusions
Framework incompatibilitiesFundamental approach differences
Value priority differencesDifferent hierarchies
Definitional inconsistenciesSame term, different meanings
Methodological disagreementsHow to study the question

Note whether contradictions are apparent or fundamental

3. Reinforcement Patterns

Identify mutually supporting elements:

  • Complementary evidence
  • Multi-source claim verification
  • Framework compatibility
  • Methodological triangulation
  • Converging conclusions from different approaches
  • Progressive refinement across sources

Rate reinforcement strength and source independence


Synthesis Elements

1. Emergent Themes

Patterns not prominent in individual pieces:

  • Implicit value structures
  • Recurring unacknowledged assumptions
  • Evolving discourse patterns
  • Shifts in emphasis
  • Boundary conditions of consensus
  • Questions raised but never answered

2. Knowledge Gaps

Map the negative space:

  • Consistently unaddressed questions
  • Missing methodological approaches
  • Excluded stakeholder perspectives
  • Underdeveloped theoretical connections
  • Limited evidential support areas
  • Potential blind spots

Prioritize by significance and addressability

3. Insight Amplification

Elements that gain significance across sources:

  • Ideas recurring in different contexts
  • Concepts serving as connective tissue
  • Formulations clarifying across domains
  • Evidence gaining cumulative strength
  • Questions revealing deeper patterns
  • Frameworks with broad applicability

Integration Protocol

1. Cross-Reference Index

StructurePurpose
Concept-to-source indexFind where ideas appear
Claim verification pathwaysTrace evidence chains
Contradiction mapsSee where sources disagree
Evidence chainsFollow proof patterns
Framework comparisonsCompare approaches
Question-answer networksTrack inquiry paths

2. Knowledge Graph Construction

Create navigable relationship models:

  • Core concept clusters
  • Evidence-claim networks
  • Source relationship maps
  • Temporal development patterns
  • Framework overlaps
  • Question exploration pathways

3. Narrative Pathways

Map exploration routes:

  • Progressive depth pathways
  • Contrasting perspective sequences
  • Framework comparison journeys
  • Evidence evaluation trails
  • Concept development traces
  • Question-driven routes

Documentation Template

Collection Metadata

## Collection: [Name]

**Sources:** [Number and types]
**Date Range:** [Publication dates]
**Analysis Period:** [When analyzed]
**Primary Domains:** [Subject areas]
**Analysis Purpose:** [Intended use]

Synthesis Element

## [Element Type]: [Theme/Connection/Pattern]

**Sources:** [Contributing sources with locations]
**Evidence:** [Key supporting examples]
**Significance:** [Why this matters]
**Tensions:** [Contradictions or complications]
**Exploration Vectors:** [Further investigation directions]

Application Guidelines

Content Creation Support

For developing new content:

  • Identify strongest evidence chains for claims
  • Map contradictory perspectives for balance
  • Locate terminological consensus for clarity
  • Find conceptual bridges for interdisciplinary work
  • Pinpoint high-value unanswered questions
  • Trace intellectual lineages for attribution

Research Direction Setting

For guiding investigation:

  • Prioritize knowledge gaps by significance
  • Identify promising conceptual connections
  • Map methodological blind spots
  • Locate perspective imbalances
  • Find evidence weaknesses
  • Discover emergent questions

Library Organization

For structuring knowledge:

  • Create concept-based navigation
  • Develop claim verification structures
  • Build perspective comparison frameworks
  • Map evidence quality distributions
  • Organize by question rather than topic
  • Structure around insight clusters

Anti-Patterns

1. Collection Without Curation

Pattern: Including all available sources without assessing their quality, relevance, or redundancy. Why it fails: Bad sources contaminate synthesis. Redundant sources create false consensus. Irrelevant sources distract from patterns that matter. Fix: Assess corpus composition explicitly. Remove low-quality sources. Weight sources by independence. Note when "multiple sources" are actually one source repeated.

2. Pattern Hallucination

Pattern: Finding patterns that exist only in the selection of sources, not in the underlying reality. Why it fails: Confirmation bias shapes what sources you find. If you search for "X causes Y," you'll find sources discussing X and Y. That's not evidence of a pattern. Fix: Actively seek disconfirming sources. Note absence of pattern where expected. Distinguish "all my sources agree" from "I selected sources that agree."

3. Averaging Instead of Mapping

Pattern: Synthesizing contradictory sources into a middle position—"the truth is somewhere between." Why it fails: Contradictions often indicate real disagreement, not measurement error. The middle position may be held by no one and supported by no evidence. Fix: Map contradictions explicitly. Understand why sources disagree. Present the landscape of positions rather than an artificial consensus.

4. Evidence Chain Collapse

Pattern: Citing a synthesis as if it were primary evidence, losing the chain back to original sources. Why it fails: Meta-analysis is only as good as its sources. When the chain collapses, you can't evaluate reliability or identify where disagreement actually lies. Fix: Maintain source-to-claim indices. Always know which original source supports which synthesis claim. Make verification pathways explicit.

5. Gap Neglect

Pattern: Focusing on what sources say without mapping what they don't say—the knowledge gaps and blind spots. Why it fails: What's missing is often more important than what's present. Systematic gaps reveal biases, under-researched areas, and opportunities. Fix: Explicitly map negative space. What questions do no sources address? What methodologies are absent? What perspectives are unrepresented?

Integration

Inbound (feeds into this skill)

SkillWhat it provides
researchIndividual source discovery and query expansion
claim-investigationVerified individual claims for synthesis
fact-checkQuality-checked individual analyses

Outbound (this skill enables)

SkillWhat this provides
researchIdentified gaps for further investigation
(content creation)Synthesized knowledge for original work
(knowledge organization)Structure for information architecture

Complementary

SkillRelationship
researchResearch finds sources; meta-analysis synthesizes them. Use iteratively—synthesis reveals gaps that research fills
claim-investigationClaim-investigation verifies individual claims; meta-analysis traces how claims connect across sources

平台分布

Codex

35.08%
按下载量换算509

Claude

28.05%
按下载量换算407

Cursor

19.27%
按下载量换算279

Gemini CLI

8.23%
按下载量换算119

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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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