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continuous-agent-loop

Create and manage autonomous agent loops with quality gates and recovery controls.

3|1|Updated Mar 4, 2026
Search Tags:#ai development#evaluation#autonomous agents#quality gates#error recovery#agent loop
One-click install
npx skills add https://github.com/oabdelmaksoud/AGI-FARM-PLUGIN --skill continuous-agent-loop-oabdelmaksoud
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: continuous-agent-loop
Source: https://github.com/oabdelmaksoud/AGI-FARM-PLUGIN/tree/main/ecc-resources/skills/continuous-agent-loop
Command: npx skills add https://github.com/oabdelmaksoud/AGI-FARM-PLUGIN --skill continuous-agent-loop-oabdelmaksoud

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenges of creating and managing continuous, autonomous agent loops by providing structured patterns for quality control, evaluation, and error recovery.

Core Features & Use Cases

  • Structured Loop Patterns: Offers different loop strategies like continuous-pr, rfc-dag, infinite, and sequential based on specific needs.
  • Production Stack Integration: Recommends a robust stack including RFC decomposition, quality gates, evaluation harnesses, and session persistence.
  • Failure Mode Management: Identifies common issues like loop churn, repeated failures, and cost drift.
  • Recovery Mechanisms: Provides strategies for freezing loops, auditing, reducing scope, and replaying with acceptance criteria.
  • Use Case: Implementing a fully autonomous agent that continuously refactors code, ensuring quality through automated checks and self-correction mechanisms.

Quick Start

Use the continuous-agent-loop skill to start a sequential autonomous loop for code generation.

Frequently Asked Questions about continuous-agent-loop

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build autonomous agent loops that handle errors without churning?▼

To build autonomous agent loops, implement structured patterns with quality gates and error recovery. Prevent churn using loop freezing, scope reduction, and replaying with acceptance criteria.

What are common failure modes in continuous autonomous AI development?▼

Common failure modes in continuous autonomous AI development include loop churn, repeated retries, and cost drift. Address these by integrating quality gates, evaluation harnesses, and session persistence.

Can I use continuous agent loops for CI/PR control and RFC decomposition?▼

Yes, continuous agent loops support CI/PR control and RFC decomposition patterns. These strategies allow autonomous agents to sequentially execute tasks while ensuring quality through automated checks.

How do I stop an autonomous agent loop from repeating the same failures?▼

Stop repeated failures in autonomous agent loops using recovery mechanisms like freezing loops, auditing execution, reducing scope, and replaying with strict acceptance criteria.

What is the best way to manage cost drift in continuous autonomous agents?▼

Manage cost drift in continuous autonomous agents by integrating evaluation harnesses and quality gates. These controls monitor execution and trigger loop freezing or scope reduction when limits are exceeded.

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