autonomous-agents

$npx mdskill add benjaminasterA/antigravity-awesome-skills/autonomous-agents

Build autonomous agents that decompose goals and self-correct reliably.

  • Solves unreliable multi-step agent loops that fail without human intervention.
  • Depends on agent loops, goal decomposition, and self-correction patterns.
  • Decides actions by alternating reasoning and execution with guardrails.
  • Delivers consistent results through reflection and iterative improvement.

SKILL.md

.github/skills/autonomous-agentsView on GitHub ↗
---
name: autonomous-agents
description: "Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it'..."
source: vibeship-spawner-skills (Apache 2.0)
risk: unknown
---

# Autonomous Agents

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`

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

More from benjaminasterA/antigravity-awesome-skills

SkillDescription
2d-games2D game development principles. Sprites, tilemaps, physics, camera.
3d-games3D game development principles. Rendering, shaders, physics, cameras.
3d-web-experienceExpert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing ...
accessibility-compliance-accessibility-auditYou are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.
active-directory-attacksThis skill should be used when the user asks to \"attack Active Directory\", \"exploit AD\", \"Kerberoasting\", \"DCSync\", \"pass-the-hash\", \"BloodHound enumeration\", \"Golden Ticket\", ...
activecampaign-automationAutomate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
address-github-commentsUse when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
agent-framework-azure-ai-pyBuild Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code int...
agent-manager-skillManage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
agent-memory-mcpA hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).