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Agents

Design, build, and deploy AI agents with architecture patterns, framework selection, memory systems, and production safety.

作者: admin | 来源: ClawHub
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V 1.0.0
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Agents

## 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 — Decision Checklist - [ ] **Single purpose defined?** If you can't say it in one sentence, split into multiple agents - [ ] **User identified?** Internal team, end customer, or another system? - [ ] **Interaction modality?** Chat, voice, API, scheduled tasks? - [ ] **Single vs multi-agent?** Start simple — only add agents when roles genuinely differ - [ ] **Memory strategy?** What persists within session vs across sessions vs forever? - [ ] **Tool access tiers?** Which actions are read-only vs write vs destructive? - [ ] **Escalation rules?** When MUST a human step in? - [ ] **Cost ceiling?** Budget per task, per user, per month? ## Critical Rules 1. **Start with one agent** — Multi-agent adds coordination overhead. Prove single-agent insufficient first. 2. **Define escalation triggers** — Angry users, legal mentions, confidence drops, repeated failures → human 3. **Separate read from write tools** — Read tools need less approval than write tools 4. **Log everything** — Tool calls, decisions, user interactions. You'll need the audit trail. 5. **Test adversarially** — Assume users will try to break or manipulate the agent 6. **Budget by task type** — Use cheaper models for simple tasks, expensive for complex ## The Agent Loop (Mental Model) ``` OBSERVE → THINK → ACT → OBSERVE → ... ``` Every agent is this loop. The differences are: - What it observes (context window, memory, tool results) - How it thinks (direct, chain-of-thought, planning) - What it can act on (tools, APIs, communication channels)

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⬇ 下载 Agents v1.0.0

文件大小: 12.81 KB | 发布时间: 2026-4-17 19:03

v1.0.0 最新 2026-4-17 19:03
Initial release: architecture patterns, frameworks comparison, use cases, implementation, security, evaluation

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