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session-mesh会话网格

Agent Skill

session-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。

总安装

329

周安装

14

GitHub Stars

4

下载量

115
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:session-mesh(会话网格)
来源仓库:https://github.com/alphaonedev/openclaw-graph
仓库路径:skills/session-mesh
安装命令:
npx skills add https://github.com/alphaonedev/openclaw-graph --skill session-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/alphaonedev/openclaw-graph --skill session-mesh

简介

session-mesh 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。
  • 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。

SKILL.md

session-mesh

Purpose

This skill manages session topologies in distributed communication systems. It enables discovery of active sessions, maintains a specialization registry, allows steering or terminating sub-agents, and handles session keys for secure interactions. Use it to build resilient mesh networks where agents communicate dynamically.

When to Use

  • When monitoring or managing distributed sessions in real-time, such as in IoT fleets or multi-agent AI systems.
  • For tasks involving sub-agent control, like rerouting traffic or scaling resources in a mesh topology.
  • In scenarios requiring session key management for authentication, e.g., secure data exchange between agents.
  • Avoid if you're working with isolated, non-distributed systems; this is optimized for interconnected environments.

Key Capabilities

  • Discover alive sessions: Query active sessions using GET /api/session-mesh/alive with query parameters like?filter=active.
  • Specialization registry: Register sub-agent specializations via POST /api/session-mesh/registry with a JSON body, e.g., {"specialization": "image-processing", "agent_id": "123"}.
  • Steer sub-agents: Redirect agents using CLI flag --direction (e.g., north/south) or API endpoint POST /api/session-mesh/steer with payload {"agent_id": "456", "direction": "east"}.
  • Kill sub-agents: Terminate agents via CLI command session-mesh kill --agent-id 789 or API DELETE /api/session-mesh/agents/789.
  • Session keys: Generate keys with POST /api/session-mesh/keys, returning a secure token for authentication.

Usage Patterns

  • Basic workflow: First, discover sessions with a GET request, then use the response to steer or kill agents as needed. Always check for alive status before actions.
  • Registry pattern: Register specializations during setup, then query the registry before assigning tasks to ensure compatibility.
  • Error-resilient pattern: Wrap API calls in try-catch blocks and retry on transient errors; use session keys in every authenticated request.
  • Sub-agent management: For mesh networks, periodically poll alive sessions and steer agents based on load, e.g., every 30 seconds via a scheduled script.
  • Key handling: Always generate a new session key per interaction and store it securely; use it in headers for subsequent API calls.

Common Commands/API

  • CLI Commands:

- List alive sessions: session-mesh list --filter alive --output json. Requires $SESSION_API_KEY set in environment. - Steer an agent: session-mesh steer --agent-id 123 --direction west. Example: First run export SESSION_API_KEY=your_key then execute. - Kill an agent: session-mesh kill --agent-id 456 --force. Use --force for immediate termination without confirmation. - Register specialization: session-mesh register --spec "data-analysis" --agent-id 789. Config format: YAML file with key-value pairs, e.g., spec: data-analysis.

  • API Endpoints:

- Discover sessions: GET https://api.example.com/api/session-mesh/alive?filter=active. Headers: {'Authorization': 'Bearer $SESSION_API_KEY'}. - Code snippet (Python): import requests; import os response = requests.get('https://api.example.com/api/session-mesh/alive', headers={'Authorization': f'Bearer {os.environ.get("SESSION_API_KEY")}'}) print(response.json()) - Steer agent: POST https://api.example.com/api/session-mesh/steer with body {"agent_id": "123", "direction": "north"}. Response includes status code 200 on success. - Code snippet (curl): curl -X POST https://api.example.com/api/session-mesh/steer \ -H "Authorization: Bearer $SESSION_API_KEY" \ -d '{"agent_id": "123", "direction": "north"}' - Config format: JSON payloads for API, e.g., {"session_key": "abc123", "ttl": 3600} for key generation.

Integration Notes

  • Authentication: All commands and APIs require a session key. Set it via environment variable: export SESSION_API_KEY=your_secure_key. Never hardcode keys; use secure vaults.
  • Dependencies: Integrate with distributed-comms cluster by including the skill ID "session-mesh" in your AI agent's config file, e.g., JSON: {"skills": ["session-mesh"], "cluster": "distributed-comms"}.
  • Configuration: Use a YAML config for multi-session setups, e.g.: sessions: - id: 123 - filter: alive Load it with session-mesh load-config path/to/config.yaml.
  • Testing: Run integration tests in a sandbox environment; mock API responses for endpoints like /api/session-mesh/alive to simulate failures.

Error Handling

  • Common errors: HTTP 404 for non-existent agents (e.g., when killing an invalid ID); handle by checking response.status_code == 404 and logging the error.
  • Authentication failures: If $SESSION_API_KEY is invalid, expect 401 Unauthorized; resolve by regenerating the key via POST /api/session-mesh/keys and retry.
  • Prescriptive steps: Always validate inputs before commands, e.g., check if agent_id exists via a prior GET request. For CLI, use --verbose flag to debug, e.g., session-mesh list --filter alive --verbose. In code, wrap calls like this: try: response = requests.post(url, headers=headers) response.raise_for_status() except requests.exceptions.HTTPError as e: print(f"Error: {e.response.status_code} - {e.response.text}")
  • Retry logic: Implement exponential backoff for network errors; limit retries to 3 attempts.

Graph Relationships

  • Related to cluster: "distributed-comms" for interconnected agent management.
  • Connects with tags: "sessions" (shares data with session-based skills), "topology" (links to network mapping tools), "mesh" (integrates with peer-to-peer systems), "subagents" (depends on sub-agent control skills like agent-lifecycle).

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

33.04%
按下载量换算38

Claude

29.43%
按下载量换算34

Cursor

19.71%
按下载量换算23

Gemini CLI

10.6%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

通过

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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