I recently came across nanocode, a Claude-style coding agent implemented in roughly 250 lines of code. It’s impressive not because it competes with Claude Code, but because it demonstrates just how powerful modern language models have become. Give a model a small set of tools and let it iterate, and surprisingly complex behavior emerges.

The core idea

At its core, the system equips the model with a handful of tools:

  • read – read a file
  • write – write content to a file
  • edit – replace content in a file
  • glob – find files by pattern
  • grep – search files for a pattern
  • bash – run a shell command

The agent (powered by Claude) works as follows:

  1. Describe the available tools to the model (once at startup)
  2. Get a user prompt
  3. The model decides whether it needs to call a tool
  4. Execute the tool and update the context
  5. Loop back to step 3 until the model produces a final answer
  flowchart TD
    A[Describe tools to model] --> B[User prompt]
    B --> C[Model reasoning]
    C -->|Tool call| D[Execute tool]
    D --> E[Update context]
    E --> C
    C -->|No tool call| F[Final response]
    F --> B

    subgraph Setup
        A
    end

    subgraph Agent Loop
        C
        D
        E
    end

Despite its simplicity, this pattern leads to complex behavior. It also highlights an important point: the model matters. Strong reasoning and planning capabilities amplify what even minimal tooling can achieve.

If you play with this approach, it’s clear that nanocode isn’t as sophisticated as Claude Code, but it doesn’t need to be. My experience was rougher around the edges, though I was still able to generate a simple FastAPI service. With more polished tools and a better TUI, this same loop could power surprisingly capable developer workflows.

This kind of open-ended loop works especially well for exploratory tasks, where you want the agent to search, inspect, and iterate freely. I encourage you to check out the code. It’s easy to follow.