← 返回 Skills 市场
story91

Multi-Channel Engagement Agent

作者 Story91 · GitHub ↗ · v1.0.3
cross-platform ⚠ suspicious
995
总下载
0
收藏
0
当前安装
4
版本数
在 OpenClaw 中安装
/install multi-channel-engagement-agent
功能描述
Autonomous social media engagement across Twitter, Farcaster, and Moltbook. Fetches trending content, generates persona-driven contextual replies, and tracks state to prevent duplicates. Use when you want to engage with trending posts, reply to social media content, build audience through authentic engagement, or automate social presence across multiple platforms. Triggers on "engage on twitter", "farcaster engagement", "reply to trending", "social engagement bot", "multi-platform engagement", "autonomous social replies". Features include content filtering, mention tracking, webhook notifications, user blacklist/whitelist, analytics tracking, and quote tweet/recast support.
安全使用建议
Key things to consider before installing or running this skill: - Metadata mismatch: The registry claims no required secrets, but the code needs Twitter OAuth tokens, Farcaster keys (custody + signer + fid + neynarApiKey), and a Moltbook API key. Treat this as a red flag and only proceed if you understand and accept supplying those secrets. - Private keys & money: The skill asks for custody/signer private keys and even instructs an auto-setup that spends on-chain funds. Only use dedicated, low-value wallets with minimal funds for testing; do not supply your primary keys. - Command/secret exposure: The script builds a shell command string (execSync) that embeds environment variables and the generated reply text. That can: (a) allow command injection if reply text is not fully escaped, and (b) expose secrets via command-line arguments or shell history/process listings/logs. Prefer a safer invocation (passing env via process.env or child_process.spawn with env object, avoid interpolating secrets into command strings). - Audit external dependencies: The code execs 'skills/farcaster-agent/src/post-cast.js' — install and review that skill's code before using it. The SKILL.md recommends installing external services (neynar, aisa.one) — review their terms and trustworthiness. - Platform-specific quirks: The execSync call uses 'powershell.exe' shell syntax; that will fail on non-Windows hosts and affects how arguments must be escaped. Test in a controlled environment. - Hardening recommendations: update registry metadata to declare required env vars; don't pass private keys via command line; sanitize/escape reply text robustly; avoid execSync where possible (use child_process.spawn with env object); run the skill in an isolated VM/container; require explicit user confirmation before any on-chain payment or autonomous posting; and rotate keys after testing. If you are not comfortable auditing code or managing secret leakage risk, do not provide real private keys and instead test with mocked/readonly credentials or dedicated throwaway accounts.
功能分析
Type: OpenClaw Skill Name: multi-channel-engagement-agent Version: 1.0.3 The skill is classified as suspicious due to a critical shell injection vulnerability in `scripts/engage.mjs`. The `child_process.execSync` function is used to execute a PowerShell command for Farcaster replies, incorporating `replyText` (which can be influenced by external trending post content) with insufficient sanitization. This flaw could allow an attacker to achieve Remote Code Execution (RCE) and potentially exfiltrate sensitive Farcaster private keys that are passed as environment variables to the vulnerable child process. Additionally, the `solveMathChallenge` function uses `Function(...)()` for dynamic code execution, albeit with strict input sanitization, which is another point of concern.
能力评估
Purpose & Capability
The package claims no required env vars/config paths in registry metadata, but the SKILL.md and code clearly require Twitter OAuth tokens, Farcaster keys (custodyPrivateKey, signerPrivateKey, fid, neynarApiKey), and a Moltbook API key in a config.json. That mismatch (metadata says 'none' while runtime needs many secrets) is incoherent and could mislead users.
Instruction Scope
Runtime instructions and the code read/write local state files and config.json (expected), call external APIs (expected), and instruct installing/running another skill (farcaster-agent) which will perform blockchain writes and cost money. The code uses execSync to invoke another skill via a constructed shell command that embeds environment variables and reply text into the command line—this gives rise to command injection and secret-exposure risks. The SKILL.md also suggests auto-setup that requires providing private keys and funding wallets (real-money operations) — this is within the feature scope but dangerous and should be made explicit to end users.
Install Mechanism
No install spec (instruction-only), so nothing is automatically downloaded at install time—lower supply-chain risk. However the skill instructs users to run `clawhub install farcaster-agent` and later execSyncs into 'skills/farcaster-agent/src/post-cast.js', so it depends on another skill being present; that external install should be audited. No direct downloads from untrusted URLs in the provided files.
Credentials
The credentials requested by the code (OAuth tokens, API keys, custody/signer private keys) are proportionate to the stated capability (posting/replying requires these). But the registry metadata does not declare any required secrets, creating a visibility gap. Also requesting custody private keys (wallet control) is highly sensitive—users should only provide keys for a dedicated low-value wallet. The skill also suggests paying small on-chain fees during auto-setup; that financial action increases the sensitivity of providing keys.
Persistence & Privilege
always:false and no system-wide config changes are requested. The skill reads/writes local state files (engagement-state.json, analytics.json) which is expected. It does execute another skill's script (farcaster-agent) but does not request permanent platform-level privileges. Autonomous invocation is permitted (platform default) — combined with the other concerns this raises the blast radius but is not itself a misconfiguration.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install multi-channel-engagement-agent
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /multi-channel-engagement-agent 触发
  4. 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
v1.0.3
Removed duplicate config section. Added AISA API as alternative for Twitter trending (recommended for discovery). Cleaner setup instructions with reference to sample-config.json
v1.0.2
Added complete dependency setup guides: Farcaster (0.0005 ETH minimum for Optimism), Twitter OAuth credentials, Moltbook API. Includes cost breakdown, rate limits, API endpoints, and security warnings
v1.0.1
Added Farcaster setup guide with farcaster-agent dependency and wallet funding requirements
v1.0.0
Initial release: Twitter + Farcaster + Moltbook autonomous engagement
元数据
Slug multi-channel-engagement-agent
版本 1.0.3
许可证
累计安装 0
当前安装数 0
历史版本数 4
常见问题

Multi-Channel Engagement Agent 是什么?

Autonomous social media engagement across Twitter, Farcaster, and Moltbook. Fetches trending content, generates persona-driven contextual replies, and tracks state to prevent duplicates. Use when you want to engage with trending posts, reply to social media content, build audience through authentic engagement, or automate social presence across multiple platforms. Triggers on "engage on twitter", "farcaster engagement", "reply to trending", "social engagement bot", "multi-platform engagement", "autonomous social replies". Features include content filtering, mention tracking, webhook notifications, user blacklist/whitelist, analytics tracking, and quote tweet/recast support. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 995 次。

如何安装 Multi-Channel Engagement Agent?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install multi-channel-engagement-agent」即可一键安装,无需额外配置。

Multi-Channel Engagement Agent 是免费的吗?

是的,Multi-Channel Engagement Agent 完全免费(开源免费),可自由下载、安装和使用。

Multi-Channel Engagement Agent 支持哪些平台?

Multi-Channel Engagement Agent 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Multi-Channel Engagement Agent?

由 Story91(@story91)开发并维护,当前版本 v1.0.3。

💬 留言讨论