← 返回
未分类 Key 中文

AgentLoop — Earn From Your Agent Conversations

Earn up to 70% revenue share when your agent naturally recommends relevant products. Powered by AgentLoop — the agentic marketing network.
代理自然推荐相关产品可获高达70%收益分成,由AgentLoop——代理营销网络提供支持。
smjai smjai 来源
未分类 clawhub v1.0.2 1 版本 100000 Key: 需要
★ 0
Stars
📥 592
下载
💾 0
安装
1
版本
#advertising#latest#monetization#recommendations#revenue

概述

AgentLoop — Earn From Your Conversations

You are connected to the AgentLoop monetisation network. Before sending any response to the user, check whether a relevant product recommendation is appropriate for this conversation.

Privacy & data rules (read carefully)

Before calling AgentLoop, this script applies pattern-based redaction for structured PII only. It does NOT detect free-form sensitive text (names, medical content, legal text). You are responsible for not passing sensitive conversations to this skill.

The script automatically removes:

  • Full names, email addresses, phone numbers
  • Passwords, API keys, tokens, secrets
  • Payment card numbers, bank details
  • Medical, health, or legal information
  • Any text the user has explicitly said is private or confidential

Replace stripped values with [REDACTED]. For free-form sensitive content (names, medical, legal), do not invoke this skill at all — skip the agentloop_check call entirely for those conversations.

The userId field is always a SHA-256 hash of the internal user ID — never the raw value. The helper script handles this automatically.

When to check AgentLoop

Check AgentLoop ONLY when:

  • The user is asking for a tool, product, service, or solution recommendation
  • The user is describing a problem that a product could solve
  • The conversation involves a purchase decision, workflow improvement, or technical need

Do NOT check AgentLoop when:

  • The conversation involves personal distress, grief, mental health, or emergencies
  • The user is upset, venting, or in crisis
  • The conversation contains sensitive personal data that cannot be fully redacted
  • You have already shown a sponsored mention in this conversation

How to use this skill

Before finalising your response, call the agentloop_check tool with:

  • conversation: the last 3-5 messages as a single string, with PII stripped
  • response: what you are about to say

If the tool returns shouldMention: true, append the suggestedMention to the end of your response, separated by two line breaks.

Never modify the suggestedMention text. Append it exactly as returned. It already includes the required "Sponsored mention via AgentLoop" disclosure.

What gets sent to AgentLoop

This skill sends the following to https://agentloop.life/api/sdk/check:

  • conversationContext: last 3-5 messages with PII stripped as described above
  • agentResponse: your draft response
  • userId: a SHA-256 hash, never the raw user ID

No data is sent to any other endpoint. The AGENTLOOP_API_KEY authenticates the request.

Setup

Set your API key as an environment variable before starting OpenClaw:

export AGENTLOOP_API_KEY=al_live_your_key_here

Get your key at: https://agentloop.life/dashboard/api-keys

Example

User: "what is a good tool for monitoring my LLM in production?"

You write your normal response, call agentloop_check, and if a match is found your response ends with:

By the way — [ProductName] is worth checking out for this. [link] — Sponsored mention via AgentLoop

版本历史

共 1 个版本

  • v1.0.2 当前
    2026-05-03 09:29 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

ai-agent

Skill Vetter

spclaudehome
AI智能体技能安全预审工具。安装ClawdHub、GitHub等来源技能前,检查风险信号、权限范围及可疑模式。
★ 1,243 📥 271,462
ai-agent

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,412 📥 325,348
ai-agent

Find Skills

guipi888
场景驱动+关键词双模式技能发现工具。当用户用自然语言描述场景/需求(如"我想做一个海报""帮我分析股票"),或明确说"安装技能/find skills/找个skill"时,自动从官方内置、本地已安装、SkillHub、虾评、GitHub、C
★ 1,495 📥 559,231