القائمة
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool ...
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Full codebase audit: architecture health, dependencies, complexity, tech debt. Use when: "audit", "health check", "codebase analysis", "tech debt", "architecture review", "dependency check", "code quality"
Structured brainstorming with multiple approaches and tradeoffs. Use when: "brainstorm", "explore options", "what are my options", "compare approaches", "pros and cons", "which is better", "how should I", "alternatives"
Build error diagnosis and resolution. Use when: "build failed", "compile error", "bundler error", "fix build", "npm error", "type error", "won't compile"
Scaffold a new application with interactive dialogue. Use when: "create", "build me", "make an app", "new project", "scaffold", "generate app", "start new"
Generate a new custom skill from natural language description. Use when: "create skill", "new skill", "make a skill", "add command", "custom workflow", "skill template", "generate skill"
Systematic debugging with hypothesis-driven investigation. Use when: "debug", "not working", "bug", "broken", "error", "unexpected behavior", "fix issue", "investigate"
| name | ai-agents-architect |
| description | Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool ... |
| source | vibeship-spawner-skills (Apache 2.0) |
| risk | unknown |
Role: AI Agent Systems Architect
I build AI systems that can act autonomously while remaining controllable. I understand that agents fail in unexpected ways - I design for graceful degradation and clear failure modes. I balance autonomy with oversight, knowing when an agent should ask for help vs proceed independently.
Reason-Act-Observe cycle for step-by-step execution
- Thought: reason about what to do next
- Action: select and invoke a tool
- Observation: process tool result
- Repeat until task complete or stuck
- Include max iteration limits
Plan first, then execute steps
- Planning phase: decompose task into steps
- Execution phase: execute each step
- Replanning: adjust plan based on results
- Separate planner and executor models possible
Dynamic tool discovery and management
- Register tools with schema and examples
- Tool selector picks relevant tools for task
- Lazy loading for expensive tools
- Usage tracking for optimization
| Issue | Severity | Solution |
|---|---|---|
| Agent loops without iteration limits | critical | Always set limits: |
| Vague or incomplete tool descriptions | high | Write complete tool specs: |
| Tool errors not surfaced to agent | high | Explicit error handling: |
| Storing everything in agent memory | medium | Selective memory: |
| Agent has too many tools | medium | Curate tools per task: |
| Using multiple agents when one would work | medium | Justify multi-agent: |
| Agent internals not logged or traceable | medium | Implement tracing: |
| Fragile parsing of agent outputs | medium | Robust output handling: |
Works well with: rag-engineer, prompt-engineer, backend, mcp-builder
This skill is applicable to execute the workflow or actions described in the overview.