SuperAPI AI Directory

loop-agent

Agents & models

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Updated 10-15 20:30

About this skill

Loop Agent Skill

Execute workflow agents iteratively for refinement and progressive improvement until quality criteria are met.

Quick Reference

  • Modes - Loop termination modes (fixed, criteria, convergence, hybrid)
  • Patterns - Common loop patterns (refinement, test-fix, optimization)
  • Configuration - Loop setup and templates
  • Examples - Complete loop examples

When to Use

  • Code needs iterative refinement until quality standards met
  • Tests need repeated fix-validate cycles
  • Performance requires progressive optimization
  • Quality improvements need multiple passes
  • Feedback loops necessary for convergence

NOT Appropriate For

  • Single-pass tasks (use specialized agent)
  • Purely parallel work (use agent-coordination)
  • Simple linear workflows (use sequential)
  • One-time analysis

Core Concepts

Loop Termination Modes

Mode Description Use When
Fixed Run exactly N iterations Known number of passes needed
Criteria Until success criteria met Specific quality/performance targets
Convergence Stop at diminishing returns Optimal result unknown
Hybrid Combine multiple conditions Complex requirements

See modes.md for detailed mode documentation and patterns.md for common loop patterns.