# Loop Agent

> Execute workflow agents iteratively for refinement and progressive improvement until quality criteria are met. Use when tasks require repetitive refinement, multi-iteration improvements, progressive optimization, or feedback loops until convergence.

- **Type:** Skill
- **Install:** `agentstack add skill-d-o-hub-rust-self-learning-memory-loop-agent`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [d-o-hub](https://agentstack.voostack.com/s/d-o-hub)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [d-o-hub](https://github.com/d-o-hub)
- **Source:** https://github.com/d-o-hub/rust-self-learning-memory/tree/main/.agents/skills/loop-agent
- **Website:** https://d-o-hub.github.io/rust-self-learning-memory/

## Install

```sh
agentstack add skill-d-o-hub-rust-self-learning-memory-loop-agent
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Loop Agent Skill

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

## Quick Reference

- **[Modes](modes.md)** - Loop termination modes (fixed, criteria, convergence, hybrid)
- **[Patterns](patterns.md)** - Common loop patterns (refinement, test-fix, optimization)
- **[Configuration](configuration.md)** - Loop setup and templates
- **[Examples](examples.md)** - 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](modes.md)** for detailed mode documentation and **[patterns.md](patterns.md)** for common loop patterns.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [d-o-hub](https://github.com/d-o-hub)
- **Source:** [d-o-hub/rust-self-learning-memory](https://github.com/d-o-hub/rust-self-learning-memory)
- **License:** MIT
- **Homepage:** https://d-o-hub.github.io/rust-self-learning-memory/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-d-o-hub-rust-self-learning-memory-loop-agent
- Seller: https://agentstack.voostack.com/s/d-o-hub
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.