multiAI Summary Pending
ai-agents-architect
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 use, function calling.
231 stars
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/ai-agents-architect/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/sickn33/ai-agents-architect/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ai-agents-architect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ai-agents-architect Compares
| Feature / Agent | ai-agents-architect | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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 use, function calling.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AI Agents Architect **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. ## Capabilities - Agent architecture design - Tool and function calling - Agent memory systems - Planning and reasoning strategies - Multi-agent orchestration - Agent evaluation and debugging ## Requirements - LLM API usage - Understanding of function calling - Basic prompt engineering ## Patterns ### ReAct Loop Reason-Act-Observe cycle for step-by-step execution ```javascript - 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-and-Execute Plan first, then execute steps ```javascript - Planning phase: decompose task into steps - Execution phase: execute each step - Replanning: adjust plan based on results - Separate planner and executor models possible ``` ### Tool Registry Dynamic tool discovery and management ```javascript - Register tools with schema and examples - Tool selector picks relevant tools for task - Lazy loading for expensive tools - Usage tracking for optimization ``` ## Anti-Patterns ### ❌ Unlimited Autonomy ### ❌ Tool Overload ### ❌ Memory Hoarding ## ⚠️ Sharp Edges | 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: | ## Related Skills Works well with: `rag-engineer`, `prompt-engineer`, `backend`, `mcp-builder`