# Autonomous Agents > 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'... Use when this capability is needed. - Skill: `tomevault-io/autonomous-agents` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/autonomous-agents` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/autonomous-agents/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/autonomous-agents --- # 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. --- ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills) ### Memory-First Protocol Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency. ```bash # Check for prior AI agent orchestration context before starting python3 execution/memory_manager.py auto --query "agent patterns and orchestration strategies for Autonomous Agents" ``` ### Storing Results After completing work, store AI agent orchestration decisions for future sessions: ```bash python3 execution/memory_manager.py store \ --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \ --type decision --project \ --tags autonomous-agents ai-agents ``` ### Multi-Agent Collaboration This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work. ```bash python3 execution/cross_agent_context.py store \ --agent "" \ --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \ --project ``` ### Control Tower Integration Register agents and tasks with the Control Tower (`execution/control_tower.py`) for centralized orchestration across machines and LLM providers. ### Blockchain Identity Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.