Verified:GitHub

continuous-agent-loop

Configure continuous agent loops with quality gates and recovery controls.

Updated Sep 13, 2025

Search Tags:#autonomous agents #quality gates #session persistence #failure recovery #eval harness #RFC decomposition #CI pull requests

Ready to run

npx skills add https://github.com/llmh333/employee_management_spring --skill continuous-agent-loop-llmh333

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: continuous-agent-loop
Source: https://github.com/llmh333/employee_management_spring/tree/main/.gemini/skills/continuous-agent-loop
Command: npx skills add https://github.com/llmh333/employee_management_spring --skill continuous-agent-loop-llmh333

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents autonomous agent workflows from spinning endlessly or producing low-quality outputs by enforcing structured loop control, evaluation, and recovery when progress stalls.

Core Features & Use Cases

Loop selection with CI/PR and RFC options: Choose sequential, CI/PR-controlled, RFC-decomposed DAG, or exploratory parallel generation flows based on the constraints of the work.
Production-grade loop stack: Combine RFC decomposition, quality gates, an evaluation loop, and session persistence to keep generation measurable and reproducible.
Failure-mode detection and recovery: Detect churn, repeated retries with the same root cause, merge queue stalls, and cost drift, then freeze and replay with clear acceptance criteria.

Quick Start

Ask the AI to set up a continuous agent loop that selects the right flow (sequential, continuous-pr, rfc-dag, or infinite) and includes quality gates, eval harnessing, and a recovery plan for loop churn and stalled merges.

Frequently Asked Questions about continuous-agent-loop

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

FAQPage Schema

How do I stop autonomous agent loops from churning and producing low-quality outputs?▼

Autonomous agent loops require quality gates and an eval harness to prevent churn and low-quality outputs. By enforcing structured loop control with session persistence, the workflow detects stalls, freezes, and replays generation with clear acceptance criteria.

How do I set up a continuous agent loop for CI pull requests?▼

Setting up a continuous agent loop for CI pull requests involves selecting a CI/PR-controlled generation flow. This enforces quality gates and an evaluation loop to constrain autonomous generation, ensuring outputs meet acceptance criteria before merging.

What is RFC decomposition DAG planning in autonomous generation?▼

RFC decomposition DAG planning is a flow that breaks down requests for comments into a directed acyclic graph for autonomous agents. It structures generation tasks to keep outputs measurable, reproducible, and convergent toward acceptance criteria.

How do autonomous agents handle failure recovery when progress stalls?▼

Autonomous agents handle failure recovery by detecting churn, repeated retries, and cost drift, then freezing the session. They replay the generation loop using session persistence and explicit acceptance criteria to resume progress safely.

Can I use exploratory parallel generation with session persistence?▼

Yes, you can use exploratory parallel generation with session persistence. This combination ensures parallel autonomous workflows remain measurable and reproducible, allowing you to audit the evaluation loop and recover from stalls.