Autonomous Agents Agent Skill

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's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

671 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

505

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/Dokhacgiakhoa/Agent-Skills-4-Vibe-Coding-CLI --skill autonomous-agents

What comes with it

889 bytes besides the instruction

sub-skills/general-purpose-autonomy.md

sub-skills/plan-execute-pattern.md

sub-skills/react-agent-loop.md

sub-skills/reflection-pattern.md

sub-skills/trusting-agent-outputs.md

sub-skills/unbounded-autonomy.md

The instruction itself

10 sections, as written by the author

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

🧠 Knowledge Modules (Fractal Skills)

1. ReAct Agent Loop

2. Plan-Execute Pattern

3. Reflection Pattern

4. ❌ Unbounded Autonomy

5. ❌ Trusting Agent Outputs

6. ❌ General-Purpose Autonomy

Other skills for the same job

different authors, same section of the catalogue

Hook Development

by anthropics

vendor ×2

This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

Coding Agent Session Search - unified CLI/TUI to index and search local coding agent history from Claude Code, Codex, Gemini, Cursor, Aider, ChatGPT, Pi-Agent, Factory, and more. Purpose-built for AI agent consumption with robot mode.

Destructive Command Guard - High-performance Rust hook for Claude Code that blocks dangerous commands before execution. SIMD-accelerated, modular pack system, whitelist-first architecture. Essential safety layer for agent workflows.

Makepad UI development skills for Rust apps: setup, patterns, shaders, packaging, and troubleshooting.

Secure environment variable management ensuring secrets are never exposed in Claude sessions, terminals, logs, or git commits

Prompt for generating an AGENTS.md file for a repository

2k tokens

How to use it

Copy the folder

Take dokhacgiakhoa/autonomous-agents from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.