Design production LLM agent loop patterns, tool schemas, and OWASP risk mappings.
npx skills add https://github.com/Muvon/octomind-tap --skill ai-agent-design-muvon
Please help me install this Agent Skill. Skill: ai-agent-design Source: https://github.com/Muvon/octomind-tap/tree/main/skills/ai-agent-design Command: npx skills add https://github.com/Muvon/octomind-tap --skill ai-agent-design-muvon
This Skill helps you design and harden production LLM agents by turning agent behavior into reliable loop patterns, well-specified tool schemas, and safe orchestration with strong failure containment.
Use this Skill to harden a new agent by asking your AI to produce an agent design package (loop pattern, tool schemas, termination strategy, observability hooks, and OWASP risk mapping) for your specific workflow and tools.
High-intent search queries and answers about installing and using this skill.
Prevent infinite loops in LLM agents by defining strict termination predicates, structured error feedback, and loop containment controls. Applying specific agent loop patterns like ReAct or Plan-and-Execute ensures your agent reliably stops calling tools when a task completes or fails.
Structure JSON Schema tool interfaces for LLM agents by enforcing strict modes, writing clear descriptions, and optimizing context-window strategy. Proper tool schema engineering reduces ambiguity and mitigates prompt injection risks during agent orchestration.
OpenTelemetry GenAI observability for agents works by injecting semantic convention hooks into your agent loop patterns. This traces tool-calling behavior, monitors operational readiness, and maps execution flows to identify orchestration failures.
Yes, you can use MCP for multi-agent orchestration to coordinate complex planning workflows. MCP-orchestrated multi-agent planning ensures robust behavior across practical scenarios by managing tool schemas and risk surfaces safely.
You need OWASP risk mapping for LLM agent design when moving systems to production to identify unsafe risk surfaces. Mapping risks to the OWASP LLM and Agentic Top 10 ensures your agent loop patterns and tool schemas maintain strict operational security.
Agents call wrong tools when tool schemas lack strict modes or context-window strategies are misaligned. Debug misbehaving agents by refining JSON Schema descriptions and applying structured loop patterns like Reflexion to reduce ambiguity in tool selection.
BoraPerusicGenerate autonomous coding agent architectures with tool schemas and safety controls.
kagentiInstrument GenAI agents with OpenTelemetry semantic conventions for LLM trace data.
ContextJet-aiAdd OpenTelemetry tracing to LLM applications capturing prompts, tool calls, token usage, latency, and cost.
wuzhong-orderlyProvide React UI components and hooks for Orderly Network DEX applications.
