Design autonomous AI agents that break goals into tasks, use tools, and review their own work. Covers reasoning and action loops, separate planning and execution, and reliability measures such as cost limits, validation, and logging.
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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
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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
Alternating reasoning and action steps
Separate planning phase from execution
Self-evaluation and iterative improvement
| 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 |
Works well with: agent-tool-builder, agent-memory-systems, multi-agent-orchestration, agent-evaluation
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Create interactive 3D scenes for websites, including product views and scroll-driven animations. Covers choosing Three.js, React Three Fiber, or Spline, preparing lightweight models, showing loading progress, and adapting experiences for mobile devices.
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Plan A/B tests that compare page or product changes, with clear hypotheses, sample sizes, success metrics, and traffic allocation. Get a structured test plan and guidance for interpreting results and deciding what to try next.
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Prepare an academic CV for faculty, postdoctoral, or research applications. Organize publications, grants, teaching, and research experience, with section order and formatting adapted to the role and academic field.
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Audit and improve web accessibility using WCAG 2.1 guidelines. Covers image descriptions, color contrast, keyboard controls, forms, and screen reader support, with code examples and automated and manual checks to guide fixes.
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Audit websites for accessibility barriers and improve image descriptions, color contrast, forms, keyboard navigation, and screen reader support. Provides code examples and automated and manual testing guidance for work toward WCAG 2.1 AA or AAA accessibility standards.
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Design autonomous agents for Claude Code plugins, including when they should run, what tools they may use, and how they should respond. Provides configuration templates, prompt guidance, and validation steps for creating agent files.
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