What agent loops does this skill cover?

It covers ReAct, which alternates reasoning and action steps, and Plan-Execute, which separates a planning phase from execution. It also covers reflection patterns for self-evaluation and iterative improvement.

Why does it emphasize reliability over capability?

Because every extra decision multiplies failure probability. A 95% success rate per step drops to about 60% by step 10, so compounding error rates are what kill autonomous agents.

Autonomous Agents

SkillAI & models

This skill is a guide for building reliable autonomous AI agents. It covers agent loops such as ReAct and Plan-Execute, goal decomposition, and reflection patterns. The focus is on reliability over capability, because per-step error rates compound as an agent takes more steps. It pushes for guardrails, logging, and least-privilege access before adding autonomy.

Use Autonomous Agents in Claude, ChatGPT or Ahel Desktop

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Also: Claude Code · Cursor · Codex

Then ask your AI: use the Autonomous Agents skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

No other account needed.

Have an AI agent that can load skills and follow written instructions.

Autonomous AgentsStart free

What your AI can do with it

Explain the ReAct agent loop of alternating reasoning and action steps
Describe the Plan-Execute pattern that separates planning from execution
Cover reflection patterns for self-evaluation and iterative improvement
Show how goal decomposition breaks a goal into smaller steps
Warn how compounding per-step error rates reduce overall success
Recommend guardrails, logging, and least-privilege access

Getting started

Have an AI agent that can load skills and follow written instructions.
Add the autonomous-agents skill to that agent's available skills.
Ask the agent to design an agent loop, such as ReAct or Plan-Execute, for your task.
Have the agent apply goal decomposition and reflection patterns to the design.
Configure guardrails, logging, and least-privilege access before adding more autonomy.

What this skill tells your AI

The instructions your AI receives, as published by davila7/claude-code-templates in cli-tool/components/skills/ai-research/autonomous-agents/SKILL.md and read by ahel’s review.

You are an agent architect who has learned the hard lessons of autonomous AI. You've seen the gap between impressive demos and production disasters. You know that a 95% success rate per step means only 60% by step 10.

Your core insight: Autonomy is earned, not granted. Start with heavily constrained agents that do one thing reliably. Add autonomy only as you prove reliability. The best agents look less impressive but work consistently.

You push for guardrails before capabilities, logging befor

Capabilities

autonomous-agents
agent-loops
goal-decomposition
self-correction
reflection-patterns
react-pattern
plan-execute
agent-reliability
agent-guardrails

Patterns

ReAct Agent Loop

Alternating reasoning and action steps

Plan-Execute Pattern

Separate planning phase from execution

Reflection Pattern

Self-evaluation and iterative improvement

Anti-Patterns

❌ Unbounded Autonomy

❌ Trusting Agent Outputs

❌ General-Purpose Autonomy

⚠️ Sharp Edges

Issue	Severity	Solution
Issue	critical	## Reduce step count
Issue	critical	## Set hard cost limits
Issue	critical	## Test at scale before production
Issue	high	## Validate against ground truth
Issue	high	## Build robust API clients
Issue	high	## Least privilege principle
Issue	medium	## Track context usage
Issue	medium	## Structured logging

Related Skills

Works well with: agent-tool-builder, agent-memory-systems, multi-agent-orchestration, agent-evaluation

Signals

GitHub stars: 32k
Forks: 4k
Last commit: Oct 2026

Others that do the same job

autonomous-agents
Skill · agent-skills-hub

Questions

What agent loops does this skill cover?: It covers ReAct, which alternates reasoning and action steps, and Plan-Execute, which separates a planning phase from execution. It also covers reflection patterns for self-evaluation and iterative improvement.
Why does it emphasize reliability over capability?: Because every extra decision multiplies failure probability. A 95% success rate per step drops to about 60% by step 10, so compounding error rates are what kill autonomous agents.

Advanced

Item type: skill
Key: autonomous-agents-davila7
Source: github.com/davila7/claude-code-templates

github.com/davila7/claude-code-templates