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I ran an experiment to see if an AI agent could make money autonomously using Claude Code.
The results were mixed. But the lessons on skill design were huge.
A skill in Claude Code is a simple markdown file in ~/.claude/skills/. It contains instructions for the AI. The magic is not the file format. The magic is how you structure the instructions.
Effective skills need three layers to work.
- Strict Guardrails Agents drift without limits. They burn tokens on dead ends. You must define:
- Deadline: When to stop trying.
- Token budget: The maximum spend before stopping.
- Success criteria: Exactly what "done" looks like.
- Failure modes: What to do when things go wrong.
Explicit Decision Trees Do not tell an agent to "try its best." That leads to failure. Use "if X, do Y. If not X, do Z." Every phase must have a clear deliverable and a time box.
Self-Reflection An agent must learn from its own output. After every run, the agent should record:
- Income vs expected profit.
- Total token cost.
- Where it got stuck.
- What to change for next time.
This creates a compounding effect. Each skill inherits the patterns and workflows of the previous one.
My experiment showed two different results:
- Success: GitHub translations. I translated a README for under $0.13 in tokens. It worked because the task was predictable.
- Failure: Bug bounties. I spent 81K tokens and found nothing. The bounty market is too crowded. When hundreds of agents compete for one prize, being good is not enough. You must be first.
The goal is token economics. Every 100K tokens costs real money. A skill that spends 500K tokens to earn $50 is a failure.
The most efficient pattern is: read once, produce once. Every extra search or question eats your profit.
Building AI agents is not about prompt engineering. It is about systems design. You need clear guardrails, tight feedback loops, and honest reflection.
Source: https://dev.to/lin_zhongjiong_3be1375c95/how-to-build-autonomous-ai-agent-skills-for-claude-code-6h2
Optional learning community: https://t.me/GyaanSetuAi