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How to Reduce Token Usage in OpenCode with Dynamic Context Pruning (DCP)

#ai #llm #productivity #softwaredevelopment

If you’ve been using OpenCode for AI-assisted development, you’ve probably noticed one thing:

👉 Token usage can get out of hand—fast.

Between full file context, chat history, and agent loops, even simple tasks can burn thousands of tokens.

The good news? There’s a practical way to fix this:

Dynamic Context Pruning (DCP)

🧠 What is Dynamic Context Pruning?

Dynamic Context Pruning (DCP) is a strategy (usually implemented as a plugin or middleware) that:

  • Removes irrelevant context before sending it to the LLM
  • Keeps only what’s necessary (active code, recent errors, decisions)
  • Enforces token limits automatically

Think of it as a smart filter for your prompts.

⚠️ Important: It’s NOT enabled by default

Here’s where many developers get confused:

👉 OpenCode does not ship with DCP turned on out of the box.

You need to:

  1. Install a plugin (or equivalent)
  2. Register it
  3. Configure it properly

⚙️ Step-by-step: Enable DCP in OpenCode

1. Install a DCP plugin

Depending on your setup (Node/Python), install a pruning plugin:

npm install opencode-dcp-plugin
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or

pip install opencode-dcp
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2. Register the plugin

Add it to your OpenCode config:

{
  "plugins": ["dcp-plugin"]
}
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or YAML:

plugins:
  - dcp-plugin
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3. Configure pruning rules

This is where the magic happens 👇

dcp:
  max_tokens: 8000
  strategy: smart
  keep:
    - active_file
    - recent_errors
  drop:
    - old_history
    - debug_logs
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What this does:

  • ✅ Keeps relevant working context
  • ❌ Removes noise (logs, stale history)
  • 🎯 Caps total tokens before sending to model

4. Enable DCP for agents (if applicable)

If you're using agents, don’t skip this:

agents:
  coder:
    dcp: true
  debugger:
    dcp: true
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Otherwise, agents may still send full context.

5. Verify it’s working

Run a task and check logs. You should see something like:

[DCP] Reduced context: 18,240 → 6,120 tokens
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No log = not working ❌

🧪 Minimal setup (quick win)

If you want a simple config that works immediately:

plugins:
  - dcp-plugin

dcp:
  strategy: aggressive
  max_tokens: 6000
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👉 This alone can reduce token usage by 50–70% in many cases.

🚫 Common mistakes

❌ Installed plugin but didn’t register it

→ Nothing happens

❌ Agents not configured

→ Token usage still high

❌ Keeping too much context

→ You defeat pruning

❌ Sending entire repo anyway

→ DCP can’t fix bad input

🧠 Pro tips for even better results

  • Scope your prompts to specific files/functions
  • Avoid dumping entire codebases
  • Limit agent steps
  • Disable unnecessary tools

🏁 Final thoughts

Dynamic Context Pruning isn’t magic—but it’s one of the highest-impact optimizations you can apply in OpenCode.

👉 Default OpenCode: 🔥 burns tokens
👉 Optimized with DCP: ⚡ efficient and scalable

If you're building larger projects or using multi-agent workflows, enabling DCP is almost mandatory.

💬 Have you tried optimizing token usage in OpenCode? What worked for you?

AI #OpenCode #LLM #DevTools #Productivity #MachineLearning

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