Agents
by @ivangdavila
Design, build, and deploy AI agents with architecture patterns, framework selection, memory systems, and production safety.
clawhub install agentsπ About This Skill
name: Agents description: Design, build, and deploy AI agents with architecture patterns, framework selection, memory systems, and production safety.
When to Use
Use when designing agent systems, choosing frameworks, implementing memory/tools, specifying agent behavior for teams, or reviewing agent security.
Quick Reference
| Topic | File |
|-------|------|
| Architecture patterns & memory | architecture.md |
| Framework comparison | frameworks.md |
| Use cases by role | use-cases.md |
| Implementation patterns & code | implementation.md |
| Security boundaries & risks | security.md |
| Evaluation & debugging | evaluation.md |
Before Building β Decision Checklist
Critical Rules
1. Start with one agent β Multi-agent adds coordination overhead. Prove single-agent insufficient first. 2. Define escalation triggers β Angry users, legal mentions, confidence drops, repeated failures β human 3. Separate read from write tools β Read tools need less approval than write tools 4. Log everything β Tool calls, decisions, user interactions. You'll need the audit trail. 5. Test adversarially β Assume users will try to break or manipulate the agent 6. Budget by task type β Use cheaper models for simple tasks, expensive for complex
The Agent Loop (Mental Model)
OBSERVE β THINK β ACT β OBSERVE β ...
Every agent is this loop. The differences are:
β‘ When to Use
Use when designing agent systems, choosing frameworks, implementing memory/tools, specifying agent behavior for teams, or reviewing agent security.