5 API Tools That Save AI Developers Hours of Boilerplate

When I started building AI agents, I noticed a pattern: 80% of my time wasn't going into the agent logic — it was going into the infrastructure around the agent logic . Counting tokens before making API calls. Writing JSON schemas by hand. Debugging regex patterns. Cleaning up GPT output so it was actually useful. None of this is interesting work. It's the tax you pay to build something interesting. I built Agent Toolbelt to eliminate that tax. Each tool is a focused, pay-per-call API endpoint that does one thing well. Here are the five I reach for constantly. 1. Token Counter — Know Your Context Limits Before You Hit Them If you've ever gotten a context_length_exceeded error mid-agent-run, you know the pain. Token counting feels like it should be trivial, but every model counts differently, and the tiktoken library has non-obvious behavior for different models. The API: curl -X POST https://agent-toolbelt-production.up.railway.app/api/tools/token-counter \ -H "Authorization: Bearer YO