← 返回 Skills 市场

Agent Shared Context

Name: Agent Shared Context
Author: gum97

作者 Gum97 · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ 安全检测通过

148

总下载

当前安装

版本数

在 OpenClaw 中安装

/install agent-shared-context

功能描述

Cross-agent context sharing via shared files. Agents write trends, highlights, and signals to a shared folder. Other agents read before acting — creating coo...

使用说明 (SKILL.md)

Agent Relay — Cross-Agent Context Sharing

Lightweight file-based coordination for multi-agent OpenClaw setups.

Problem

Agents run independently — Reddit doesn't know what Moltbook found, News doesn't know what's trending on HN. Each agent is an island.

Solution

Shared JSON files that agents write to and read from. No config changes needed — just files on disk.

Setup

# Create shared directory in workspace
mkdir -p ~/.openclaw/workspace/shared

# Script location
~/.openclaw/workspace/scripts/shared-context.py

Usage

Agent writes after finishing work:

# Reddit agent logs trending topic
python3 scripts/shared-context.py add-trend \
  --source reddit --topic "self-hosting mini PCs" --score 1500

# News agent logs highlight
python3 scripts/shared-context.py add-highlight \
  --source news --title "Unsloth Studio launched" \
  --summary "Open-source LLM training UI, 2x faster"

Agent reads before acting:

# Moltbook agent checks what's trending before posting
python3 scripts/shared-context.py get-trends --limit 5

# Any agent checks recent highlights
python3 scripts/shared-context.py get-highlights --limit 5

Cleanup (brain-maintenance cron):

# Remove entries older than 48 hours
python3 scripts/shared-context.py cleanup --hours 48

Integration into cron prompts

Add to any agent's cron prompt:

Before posting/engaging, check shared context:
exec('python3 /path/to/scripts/shared-context.py get-trends --limit 3')
→ If a trend is relevant to this platform, create content about it.

After finishing, log what you found:
exec('python3 /path/to/scripts/shared-context.py add-trend --source \x3Cagent> --topic "\x3Cfinding>" --score \x3Crelevance>')

Files

File	Purpose
`shared/trends.json`	Topics trending across platforms
`shared/highlights.json`	Best content found by any agent
`scripts/shared-context.py`	CLI to read/write shared context

Architecture

Reddit ──write──→ shared/trends.json ←──read── Moltbook
News   ──write──→ shared/highlights.json ←──read── Clawstr
                        ↑
              brain-maintenance (cleanup)

No database. No message queue. Just JSON files on disk. Works because all agents run on the same machine.

安全使用建议

This skill is a simple, coherent file-based relay for agents, but it assumes a trust boundary: any agent or user with write access to the shared directory can influence all others. Before installing, ensure the shared folder is accessible only to trusted agents/users (set filesystem permissions), avoid constructing shell exec strings with unescaped/untrusted input (use safe argument passing), and consider adding file locks or atomic writes if you expect concurrent writes. If you need stronger guarantees, consider authenticated or signed entries or a small local service with access controls instead of plain JSON files.

功能分析

Type: OpenClaw Skill Name: agent-shared-context Version: 1.0.0 The skill bundle provides a legitimate and transparent mechanism for local inter-agent coordination using shared JSON files. The Python script (scripts/shared-context.py) implements basic CRUD operations for 'trends' and 'highlights' without any network activity, data exfiltration, or suspicious execution patterns. The instructions in SKILL.md are consistent with the tool's stated purpose of enabling multi-agent workflows.

能力评估

✓ Purpose & Capability

Name/description match the provided code and instructions. The script reads/writes JSON in a shared workspace directory and the SKILL.md tells agents to call that CLI — all required capabilities are present and proportionate to cross-agent coordination.

ℹ Instruction Scope

Instructions direct agents to exec the included Python CLI to get/add/cleanup entries in shared JSON files — this is expected. Two notes: (1) the SKILL.md encourages embedding exec('python3 /path/to/scripts/...') in agent prompts which can introduce command-construction/injection risks if agent inputs are interpolated unsafely; (2) the script performs no file locking, so concurrent writers could race or corrupt state in multi-agent setups.

✓ Install Mechanism

No install spec or remote downloads; the skill is instruction-only with a small included Python script. Nothing is written to disk beyond the shared JSON files the skill itself manages.

✓ Credentials

No environment variables, credentials, or config paths are requested. The script uses only files under the workspace/shared directory, consistent with its stated purpose.

✓ Persistence & Privilege

The skill is user-invocable and not always-enabled. It only creates/updates files within its own shared workspace; it does not modify other skills or system-wide settings.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install agent-shared-context
安装完成后，直接呼叫该 Skill 的名称或使用 /agent-shared-context 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Initial release: cross-agent context sharing via shared JSON files. Trends, highlights, cleanup.

元数据

Slug agent-shared-context

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题