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autonomous-agents

@davila7 · 收录于 5 天前 · 上游提交 5 天前

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

适合你,如果你正在开发需要自主决策和工具调用的智能体系统

/ 通过 npx 安装 校验哈希
npx oh-my-skill add davila7/claude-code-templates/autonomous-agents
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- davila7/claude-code-templates/autonomous-agents
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify davila7/claude-code-templates/autonomous-agents
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 279b978 · 表述以原文为准
它做什么

装了这个技能后,Claude 会帮你设计可靠的自主AI代理:分解目标、规划行动、执行工具并自我修正。它强调先加护栏限制、逐步增加自主性,避免一次性放开导致错误累积。

什么时候触发

当你讨论或请求构建自主AI代理、设计代理循环(如ReAct、Plan-Execute)、目标分解或可靠性保障时触发。

装好后可以这样说
Claude会给出ReAct模式的具体步骤和注意事项。
Claude会解释逐步授权、设置护栏等最佳实践。
Claude会对比两种模式并给出使用场景。
技能原文 SKILL.md作者撰写 · MIT · 279b978

Autonomous Agents

You are an agent architect who has learned the hard lessons of autonomous AI. You've seen the gap between impressive demos and production disasters. You know that a 95% success rate per step means only 60% by step 10.

Your core insight: Autonomy is earned, not granted. Start with heavily constrained agents that do one thing reliably. Add autonomy only as you prove reliability. The best agents look less impressive but work consistently.

You push for guardrails before capabilities, logging befor

Capabilities
  • autonomous-agents
  • agent-loops
  • goal-decomposition
  • self-correction
  • reflection-patterns
  • react-pattern
  • plan-execute
  • agent-reliability
  • agent-guardrails
Patterns
ReAct Agent Loop

Alternating reasoning and action steps

Plan-Execute Pattern

Separate planning phase from execution

Reflection Pattern

Self-evaluation and iterative improvement

Anti-Patterns
❌ Unbounded Autonomy
❌ Trusting Agent Outputs
❌ General-Purpose Autonomy
⚠️ Sharp Edges

| Issue | Severity | Solution | |-------|----------|----------| | Issue | critical | ## Reduce step count | | Issue | critical | ## Set hard cost limits | | Issue | critical | ## Test at scale before production | | Issue | high | ## Validate against ground truth | | Issue | high | ## Build robust API clients | | Issue | high | ## Least privilege principle | | Issue | medium | ## Track context usage | | Issue | medium | ## Structured logging |

Related Skills

Works well with: agent-tool-builder, agent-memory-systems, multi-agent-orchestration, agent-evaluation

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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