sebas-aikon-intelligence/antigravity-awesome-skills

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.

First seen Jan 26, 2026

Installation

$ npx skills add sebas-aikon-intelligence/antigravity-awesome-skills --skill ai-agents-architect

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

License LICENSE
Default branch main
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents antigravity

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,571 B
  • docs SUMMARY.md 246 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 4 installs

SKILL.md

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

- 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

- 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

- 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