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messaging-agents消息 Agent

Agent Skill

messaging-agents 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。

总安装

1,317

周安装

56

GitHub Stars

2,416

下载量

461
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:messaging-agents(消息 Agent)
来源仓库:https://github.com/letta-ai/letta-code
仓库路径:skills/messaging-agents
安装命令:
npx skills add https://github.com/letta-ai/letta-code --skill messaging-agents
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/letta-ai/letta-code --skill messaging-agents

简介

用于查找、检索和筛选相关信息,适合根据关键词快速定位候选结果。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中需要信息聚合的任务场景。
  • 通过 GitHub 安装,具体用法需结合来源仓库 README 进一步核验。
  • 安装前应确认权限范围、维护状态及是否触发联网或命令执行。
  • 建议在使用前评估对本地资源和外部 API 的调用影响。

SKILL.md

Messaging Agents

This skill enables you to send messages to other agents on the same Letta server using the thread-safe conversations API.

When to Use This Skill

  • You need to ask another agent a question
  • You want to query an agent that has specialized knowledge
  • You need information that another agent has in their memory
  • You want to coordinate with another agent on a task

What the Target Agent Can and Cannot Do

The target agent CANNOT:

  • Access your local environment (read/write files in your codebase)
  • Execute shell commands on your machine
  • Use your tools (Bash, Read, Write, Edit, etc.)

The target agent CAN:

  • Use their own tools (whatever they have configured)
  • Access their own memory blocks
  • Make API calls if they have web/API tools
  • Search the web if they have web search tools
  • Respond with information from their knowledge/memory

Important: This skill is for *communication* with other agents, not *delegation* of local work. The target agent runs in their own environment and cannot interact with your codebase.

Need local access? If you need the target agent to access your local environment (read/write files, run commands), use the Task tool instead to deploy them as a subagent:

Task({
  agent_id: "agent-xxx",           // Deploy this existing agent
  subagent_type: "explore",        // "explore" = read-only, "general-purpose" = read-write
  prompt: "Look at the code in src/ and tell me about the architecture"
})

This gives the agent access to your codebase while running as a subagent.

Finding an Agent to Message

If you don't have a specific agent ID, use these skills to find one:

By Name or Tags

Load the finding-agents skill to search for agents:

letta agents list --query "agent-name"
letta agents list --tags "origin:letta-code"

By Topic They Discussed

Load the searching-messages skill to find which agent worked on something:

letta messages search --query "topic" --all-agents

Results include agent_id for each matching message.

CLI Usage (agent-to-agent)

Starting a New Conversation

letta -p --from-agent $LETTA_AGENT_ID --agent <id> "message text"

Arguments:

ArgRequiredDescription
--agent <id>YesTarget agent ID to message
--from-agent <id>YesSender agent ID (injects agent-to-agent system reminder)
"message text"YesMessage body (positional after flags)

Example:

letta -p --from-agent $LETTA_AGENT_ID \
  --agent agent-abc123 \
  "What do you know about the authentication system?"

Response:

{
  "conversation_id": "conversation-xyz789",
  "response": "The authentication system uses JWT tokens...",
  "agent_id": "agent-abc123",
  "agent_name": "BackendExpert"
}

Continuing a Conversation

letta -p --from-agent $LETTA_AGENT_ID --conversation <id> "message text"

Arguments:

ArgRequiredDescription
--conversation <id>YesExisting conversation ID
--from-agent <id>YesSender agent ID (injects agent-to-agent system reminder)
"message text"YesFollow-up message (positional after flags)

Example:

letta -p --from-agent $LETTA_AGENT_ID \
  --conversation conversation-xyz789 \
  "Can you explain more about the token refresh flow?"

Understanding the Response

  • Scripts return only the final assistant message (not tool calls or reasoning)
  • The target agent may use tools, think, and reason - but you only see their final response
  • To see the full conversation transcript (including tool calls), use the searching-messages skill with letta messages list --agent <id> targeting the other agent

How It Works

When you send a message, the target agent receives it with a system reminder:

<system-reminder>
This message is from "YourAgentName" (agent ID: agent-xxx), an agent currently running inside the Letta Code CLI (docs.letta.com/letta-code).
The sender will only see the final message you generate (not tool calls or reasoning).
If you need to share detailed information, include it in your response text.
</system-reminder>

This helps the target agent understand the context and format their response appropriately.

Related Skills

  • finding-agents: Find agents by name, tags, or fuzzy search
  • searching-messages: Search past messages across agents, or view full conversation transcripts

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.58%
按下载量换算169

Claude

28.8%
按下载量换算133

Cursor

18.15%
按下载量换算84

Gemini CLI

7.89%
按下载量换算36

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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