afrexai-agent-engineeringDesign, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent arc...
Install via ClawdBot CLI:
clawdbot install 1kalin/afrexai-agent-engineeringGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
rm -rf /Calls external URL not in known-safe list
https://afrexai-cto.github.io/context-packs/AI Analysis
The skill definition is a framework for designing AI agents and does not contain executable code or active data exfiltration instructions. The flagged signals are examples within configuration templates (e.g., 'rm -rf /') or references to external documentation, not active malicious commands. The primary risk is conceptual, encouraging the design of autonomous systems which, if built without proper safeguards, could be unsafe.
Audited Apr 17, 2026 · audit v1.0
Generated Mar 21, 2026
A solo agent designed to manage calendars, draft emails, and summarize reports for busy executives. It operates as an advisor during onboarding, gradually promoting to operator for routine tasks, ensuring high-stakes decisions remain human-approved.
A persistent multi-agent team handling customer inquiries across Slack and Discord channels. Each agent specializes in sales, support, or operations, with shared memory for consistent service and escalation protocols.
A swarm of agents orchestrating parallel research, writing, and editing for marketing campaigns. Uses a hub-and-spoke pattern with an aggregator to compile outputs, ideal for scaling content production across multiple niches.
A solo agent acting as an advisor to medical professionals, suggesting diagnoses based on patient data while requiring human approval for critical decisions. Implements strict guardrails and memory layers for compliance and accuracy.
An autopilot agent for automated trading in proven market workflows. Starts as an operator with tight bounds, graduating to autopilot after rigorous monitoring, using risk-tolerant decision styles and real-time memory updates.
Offer the agent engineering skill as a cloud-based service with tiered pricing based on autonomy levels and agent count. Revenue streams include monthly subscriptions for solo agents and enterprise plans for multi-agent teams.
Provide expert services to design, build, and deploy custom agent systems for clients. Revenue comes from project-based fees and ongoing support contracts, leveraging the skill's architecture and operational methodologies.
License the agent engineering framework to other businesses for embedding into their products. Revenue is generated through licensing fees and royalties, enabling partners to offer AI agents without in-house development.
💬 Integration Tip
Start with a solo agent in a low-risk environment to validate the architecture before scaling to multi-agent systems, ensuring guardrails are tested thoroughly.
Scored Apr 19, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Give your AI agent eyes to see the entire internet. 7500+ GitHub stars. Search and read 14 platforms: Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongS...
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap...