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Agent Skill · 研究检索

agentic-mesh(Agent 网格)

agentic-mesh 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。

agentic-mesh 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,权限为调用外部服务;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 56,324。

总安装 456周安装 19GitHub Stars 公开资料未说明下载 152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:agentic-mesh(Agent 网格)
来源仓库:https://github.com/alavida-ai/skills
仓库路径:skills/agentic-mesh
安装命令:
npx skills add https://github.com/alavida-ai/skills --skill agentic-mesh
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/alavida-ai/skills --skill agentic-mesh

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。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。提供 Agentic Mesh 生态系统的理论基础与架构定义。

安装命令:npx skills add https://github.com/alavida-ai/skills --skill agentic-mesh。注意权限范围、维护状态,避免触发联网、命令执行或文件读写。

来源仓库内路径:skills/agentic-mesh

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/alavida-ai/skills --skill agentic-mesh;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

    它需要调用外部服务,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

agentic-mesh 怎么安装?

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

agentic-mesh 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。

agentic-mesh 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

agentic-mesh 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。

agentic-mesh 用的人多吗?

公开数据是累计安装 456 次,近一周安装 19 次,下载 152 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。

agentic-mesh 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
agentic-mesh

Agent 网格 · 本页

456—调用外部服务未明确通过

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

Agentic Mesh

Reference skill for the Agentic Mesh book (Falconer, O'Reilly 2025). Provides the theoretical and architectural foundation for building agent ecosystems.

Core Definitions

  • Agentic Mesh: Interconnected ecosystem for agent discovery, collaboration, interaction, and transactions. Inherits from service mesh (APIs) and data mesh (data products).
  • Agent: LLM-powered program that independently makes decisions, plans iteratively, and executes complex tasks. Distinguished from workflows by autonomous reasoning and nondeterministic execution.
  • Agentic Quantum: Smallest meaningful unit = LLM (brain) + tools (limbs) + execution framework, containerized as a microagent.

Architecture at a Glance

Agent Anatomy (4 components)

ComponentRole
Brain (LLM)Reasoning, planning, language — stateless, multimodal
MemoryNative / short-term / long-term / episodic / procedural / semantic
Context EngineeringHot/warm/cold cache tiers, RAG, compression, slotting
ToolsSensors + actuators, MCP protocol, tool chaining

Agent Types (4)

TypeBehavior
Task-orientedClear objective, execute plan, return result
Goal-orientedCollaborative problem-solving, dynamic planning, shared workspace
SimulationVirtual models, emergent behavior analysis
ObserverContinuous monitoring, event-driven, pub/sub

Mesh Platform (6 components)

Registry, Monitor, Interactions Server, Marketplace, Workbenches (Consumer/Creator/Trust/Operator), Proxy

Agent Lifecycle

Draft -> Registered -> Published -> Certified -> Updated -> Deprecated -> Retired

Key Frameworks

Seven-Layer Trust Framework

LayerDomain
L1Identity & Authentication (cryptographic, mTLS)
L2Authorization & Access Control (RBAC/ABAC, OAuth2)
L3Purpose & Policies (data contracts, constraints)
L4Explainability (task plans, tool selection logic)
L5Observability & Traceability (logs, correlation, monitoring)
L6Certification & Compliance (evaluation, stress testing)
L7Governance & Lifecycle (bodies, ownership, escalation)

Reliability Solution

  • Problem: Combinatorial explosion — 0.99^1000 = 0.004% accuracy
  • Solution: Task decomposition -> task independence -> specialization -> deterministic execution

Patterns Catalog

  • Communication (6): Interaction, Delegation, Conversation, Attention, Broadcast, Listener
  • Role (6): Planner, Orchestrator, Executor, Observer, Judge, Enforcer
  • Organizational (8): Singleton, Team, Organization, Swarm, Ecosystem, Legal Entity, Federation, Supply Chain
  • Messaging (7): Request-response, Async, Event-driven, Message queue, Streaming, Actor model, Shared workspaces

Operating Model (5 Pillars)

Structure (people + agents) | Process (lifecycle + governance) | Technology (registry, observability) | Policy (autonomy tiers, guardrails) | Metrics (value + safety)

Scaling Units

Agent (person) -> Fleet (team) -> Ecosystem (organization) -> Supply chain (economy)

Implementation Roadmap (5 Workstreams)

  1. Strategic foundations (vision -> MVP)
  2. Technology (build -> industrialize -> secure -> model ops)
  3. Agent & fleet factories (frameworks -> DevSecOps -> factories)
  4. Organization (operating model -> change management -> training)
  5. Governance (agent governance -> fleet governance)

Reference Files

Detailed concept files — read the specific file when deeper context is needed:

FileCoversWhen to read
foundations.mdCore definitions, mesh vision, enterprise requirements, scale predictionsDefining what agentic mesh is, why it matters
agents-landscape.mdAI history, workflows vs agents, evolution stagesComparing agents to workflows, understanding agent evolution
agent-basics.mdPlanning, execution, tools, memory, learning, collaborationUnderstanding how individual agents work
agent-architecture.mdPrinciples, components, types, all pattern catalogs, state managementDesigning agents, choosing patterns
enterprise-agents.mdMicroagents, reliability, explainability, discovery, AgentOps, testingBuilding production-grade agents
ecosystem-ux.mdFleets, mesh components, lifecycle, marketplace, workbenchesDesigning the mesh platform and UX
registry-interaction.mdRegistry data model, conversations, interactions, events, super-contextsBuilding registry and communication infrastructure
security-governance.mdSeven-layer trust, zero-trust, prompt injection, certificationImplementing security and governance
operations-factory.mdOperating model, team roles, fleet structures, agent factory, SDLCSetting up operations and agent factories
practical-roadmap.mdFive workstreams, technology stack, dependencies, scale progressionPlanning implementation

Original Chapters

Full book source material lives in references/chapters/. The concept files above are curated summaries — go to chapters for verbatim detail.

ChapterFile
Forewordreferences/chapters/00-foreword.md
Prefacereferences/chapters/01-preface.md
Part I introreferences/chapters/02-part-i-defining-the-essentials.md
Ch01: Understanding Agentic Meshreferences/chapters/03-ch01-understanding-agentic-mesh.md
Ch02: Agentic Past, Present & Futurereferences/chapters/04-ch02-agentic-past-present-future.md
Ch03: Agents vs AI Workflowreferences/chapters/05-ch03-agents-versus-ai-workflow.md
Ch04: Agent Basicsreferences/chapters/06-ch04-agent-basics.md
Part II introreferences/chapters/07-part-ii-defining-agent-ecosystem.md
Ch05: Agent Architecturereferences/chapters/08-ch05-agent-architecture.md
Ch06: Enterprise-Grade Agentsreferences/chapters/09-ch06-enterprise-grade-agents.md
Ch07: Agentic Mesh Ecosystemreferences/chapters/10-ch07-agentic-mesh-ecosystem.md
Ch08: Agentic Mesh UXreferences/chapters/11-ch08-agentic-mesh-ux.md
Ch09: Agentic Mesh Registryreferences/chapters/12-ch09-agentic-mesh-registry.md
Ch10: Interaction Managementreferences/chapters/13-ch10-interaction-management.md
Ch11: Security Considerationsreferences/chapters/14-ch11-security-considerations.md
Ch12: Trust Framework & Governancereferences/chapters/15-ch12-trust-framework-governance.md
Part III introreferences/chapters/16-part-iii-building-your-agentic-mesh.md
Ch13: Operating Model & Team Structurereferences/chapters/17-ch13-operating-model-team-structure.md
Ch14: Agent Factoryreferences/chapters/18-ch14-agent-factory.md
Ch15: Practical Roadmapreferences/chapters/19-ch15-practical-roadmap.md

平台分布

Codex

36.36%
按下载量换算55

Claude

28.8%
按下载量换算44

Cursor

17.16%
按下载量换算26

Gemini CLI

9.63%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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