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Agent Skill · 研究检索

session-bridge(会话桥)

session-bridge 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

session-bridge 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,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 25,317。

总安装 3,795周安装 163GitHub Stars 公开资料未说明下载 1,330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-0
版本
1.0.0

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-bridge(会话桥)
来源仓库:https://github.com/codeinonenight/session-bridge
安装命令:
openclaw skills install session-bridge
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install session-bridge

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。

会话桥用于在切换界面或代理间移交任务时恢复上下文。适合解决 Telegram 到 WhatsApp 或 Jon 到 Eddie 等场景下的信息丢失问题。可根据关键词快速定位候选结果,提升跨环境协作连续性。使用前请确认来源仓库维护状态,避免依赖不稳定组件。

session-bridge 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install session-bridge;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

    它需要接触敏感数据,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

session-bridge 怎么安装?

在终端执行 openclaw skills install session-bridge。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

session-bridge 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

session-bridge 需要什么权限?

权限级别是接触敏感数据。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。

session-bridge 是免费的吗?

来源标注的许可证是 MIT-0。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。

session-bridge 用的人多吗?

公开数据是累计安装 3,795 次,近一周安装 163 次,下载 1,330 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。

session-bridge 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
session-bridge

会话桥 · 本页

3,795—接触敏感数据MIT-0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

name
session-bridge
description
Use when context is lost after switching surfaces (Telegram to WhatsApp, TUI to Telegram), when handing off tasks between agents (Jon → Eddie, Cipher → Eddie), when an agent needs to know what was discussed in another session, or when you want to resume a conversation on a new surface. Triggers on "catch me up", "what were we working on", "pass this to Eddie", "context switch", "session handoff", "I'm on TUI now", "continue from where we left off".

Session Bridge

Keep context coherent across surfaces (Telegram / WhatsApp / TUI) and agents (Eddie ↔ Jon ↔ Cipher ↔ Sage ↔ Picasso) using lightweight topic capsules — without syncing full transcripts or adding load to the memory system.

Core Concept

Each active work thread gets a capsule — a small JSON file keyed by topic:

tasks/bridges/
  looking-glass.json        ← Meta Ray-Ban project
  session-bridge-design.json ← This skill's design thread
  clawhub-skill-build.json  ← Active publishing task

Capsules hold only what matters: goal, status, decisions, open questions, next action. They are transient working state, not long-term memory. They do not replace MEMORY.md, daily logs, or the ontology graph — they sit on top as a coordination layer.


Script

SCRIPT=~/.openclaw/workspace/skills/session-bridge/scripts/bridge.py
python3 $SCRIPT <command> [options]

Commands

Create a capsule

python3 $SCRIPT create \
  --topic "looking-glass" \
  --goal "Wire Meta Ray-Bans as Eddie's physical presence" \
  --source "agent:main:telegram:direct:7550791652" \
  --agent main

Update a capsule (after decisions, handoffs, progress)

python3 $SCRIPT refresh \
  --topic "looking-glass" \
  --status "active" \
  --next-action "Mike to share Ray-Ban SDK access" \
  --add-decision "Use Bluetooth audio bridge, not USB" \
  --add-question "Does Ray-Ban SDK expose camera feed?" \
  --add-fact "Mike's Ray-Bans model: Meta Ray-Ban v2"

Get a briefing for session start (hydrate)

python3 $SCRIPT hydrate --topic "looking-glass"

Output (~150–350 tokens):

[Session Bridge] Topic: looking-glass
Status: active
Goal: Wire Meta Ray-Bans as Eddie's physical presence
Decisions: Use Bluetooth audio bridge, not USB
Open: Does Ray-Ban SDK expose camera feed?
Next: Mike to share Ray-Ban SDK access
Sources: agent:main:telegram:direct:7550791652
Updated: 2026-03-20T06:45Z

Cross-agent handoff

python3 $SCRIPT handoff \
  --topic "session-bridge-design" \
  --to "agent:main:telegram:direct:7550791652"

Then pass the output to sessions_send so Eddie wakes up informed.

See all active capsules

python3 $SCRIPT list
python3 $SCRIPT status --topic "looking-glass"

Clean up stale capsules

python3 $SCRIPT expire --max-age-hours 48

Bridging Surfaces (Telegram ↔ WhatsApp ↔ TUI)

Option A — Config routing (recommended first step)

Add identityLinks to openclaw.json to collapse the same human across surfaces into one canonical session per agent:

{
  "session": {
    "dmScope": "per-channel-peer",
    "identityLinks": [
      {
        "canonical": "mike",
        "peers": [
          "telegram:7550791652",
          "whatsapp:+15555550123"
        ]
      }
    ]
  }
}

This makes Telegram-Eddie and WhatsApp-Eddie share the same session — no bridging needed. TUI uses a different mechanism (main session key).

Option B — Capsule hydration on surface switch

When the same canonical session is not possible (TUI ↔ Telegram, or different agent entirely):

  1. On the outgoing surface, refresh the relevant capsule:
   python3 $SCRIPT refresh --topic <topic> --next-action "..."
  1. On the incoming surface, hydrate at session start:
   python3 $SCRIPT hydrate --topic <topic>
  1. Inject the briefing as context before responding.

Bridging Agents (Jon → Eddie, Cipher → Eddie)

When finishing a delegation task, the completing agent should:

  1. Refresh the capsule with results:
   python3 $SCRIPT refresh \
     --topic "<task-topic>" \
     --status "done" \
     --add-decision "Research complete: X is the right approach" \
     --next-action "Eddie to implement"
  1. Generate a handoff and deliver via sessions_send:
   python3 $SCRIPT handoff --topic "<task-topic>" --to "agent:main:telegram:direct:7550791652"
   # Copy output → sessions_send(sessionKey="agent:main:...", message=<output>)

Eddie reads the brief and continues — no re-explaining needed.


What Goes Where

Information typeWhere it lives
Current topic, status, next actionCapsule (transient, expires)
Decisions worth keeping long-termMEMORY.md (promote manually)
Structured facts (people, devices, projects)Ontology graph
Narrative context / observationsDaily memory log
Team operating rulesSHARED_CONTEXT.md

Capsules are not a replacement for memory — they are short-lived working state that gets discarded when a topic concludes.


Token Cost

OperationApprox. tokensWhen
Create/refresh capsule~150On handoff or decision
Hydrate (session start briefing)~200–350Once per session
Handoff message~300Cross-agent delegation
Status/list~100On demand

Hydration adds <0.2% of a 200k context window per session. Stale capsules add zero cost (they're just files).


Agent Protocol (Team Rules)

  • On delegation: create or refresh capsule before sessions_send-ing a task
  • On completion: refresh capsule with outcome + next action, then handoff
  • On surface switch: hydrate the relevant capsule at session start
  • On topic close: set --status done, let expire cleanup handle it
  • Never: dump full session transcripts into capsules (defeats the point)

Example: Full Cross-Agent Flow

Mike asks Eddie about the Looking Glass project.
Eddie doesn't remember details from last session.

1. Eddie runs: bridge.py hydrate --topic looking-glass
   → Gets: "Status: active | Next: Mike to share SDK access"
   → Continues conversation without re-explaining from scratch

Mike tells Eddie: "Let Jon research the Ray-Ban SDK."
Eddie creates a task capsule and delegates to Jon via sessions_send.

Jon finishes research.
2. Jon runs: bridge.py refresh --topic looking-glass \
     --add-decision "SDK exposes camera feed via BLE" \
     --next-action "Eddie to prototype BLE bridge"
3. Jon runs: bridge.py handoff --topic looking-glass \
     --to agent:main:telegram:direct:7550791652
4. Jon sends handoff output to Eddie via sessions_send.

Eddie receives handoff.
5. Eddie reads capsule brief, continues work without Jon re-explaining.

Setup

No dependencies beyond Python 3.8+. Works immediately after install:

openclaw skills install session-bridge
python3 ~/.openclaw/workspace/skills/session-bridge/scripts/bridge.py list

平台分布

OpenClaw

85.69%
按下载量换算1,140

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

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。目前只有一个公开来源,建议同时核对源仓库。

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