DEV Community: piratesshield

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

piratesshield — Thu, 30 Apr 2026 20:17:43 +0000

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:

Install a plugin (or equivalent)
Register it
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

pip install opencode-dcp

2. Register the plugin

Add it to your OpenCode config:

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

or YAML:

plugins:
  - dcp-plugin

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

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

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

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

👉 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

Building a Serverless API with Cloudflare Workers (Complete Guide)

piratesshield — Thu, 30 Apr 2026 17:57:13 +0000

🚀 Building a Serverless API with Cloudflare Workers (Complete Guide)

Modern applications don’t always need a traditional backend. With Cloudflare Workers, you can build fast, scalable APIs that run at the edge—without managing servers.

In this guide, you’ll learn how to build a serverless API with persistent storage using Workers + KV.

📌 Why Cloudflare Workers?

⚡ Runs on edge locations worldwide
💸 Generous free tier
🔧 No server management
🌍 Low latency for global users

Perfect for:

Browser extensions
Lightweight apps
Sync services
Logging pipelines (SIEM feeders 👀)

🏗️ Architecture Overview

Client (Browser Extension / App)
        ↓
Cloudflare Worker (API Layer)
        ↓
KV Storage (Persistent Data)

🧰 Prerequisites

Node.js installed
Cloudflare account
Wrangler CLI

Install Wrangler:

npm install -g wrangler
wrangler login

⚙️ Project Setup

wrangler init my-worker-api
cd my-worker-api

🧾 Configuration (wrangler.toml)

name = "my-worker-api"
main = "src/index.js"
compatibility_date = "2024-01-01"

[[kv_namespaces]]
binding = "DATA_STORE"
id = "your_kv_namespace_id"

What this does:

Defines your Worker entry point
Sets runtime compatibility
Connects KV storage

🗄️ Create KV Storage

wrangler kv:namespace create DATA_STORE

👉 Copy the generated namespace ID into your config.

🔐 Set Secrets (Auth)

wrangler secret put API_TOKEN

Use this token to secure your API requests.

🧠 Core API Design

Endpoint	Method	Purpose
`/api/push`	POST	Upload & merge data
`/api/pull`	GET	Retrieve stored data
`/api/status`	GET	Metadata (sync info)
`/api/ping`	GET	Health check
`/api/clear`	DELETE	Remove all data
`/api/item/:id`	DELETE	Delete specific item
`/api/toggle/:id`	PUT	Toggle item state

🧩 Key Implementation Concepts

1. CORS Support

Access-Control-Allow-Origin: *

Allows browser apps to call your API.

2. Authentication

X-API-Token: your_secret_token

Reject requests without a valid token.

3. Data Handling Strategy

Use unique IDs for deduplication
Resolve conflicts using timestamps
Limit total stored records

4. Metadata Tracking

Store:

Last sync timestamp
Total records count

🚀 Deployment

wrangler publish

Your API will be live at:

https://your-worker-name.workers.dev

🔄 Example API Calls

Push Data

curl -X POST https://your-worker/api/push \
  -H "Content-Type: application/json" \
  -H "X-API-Token: YOUR_SECRET" \
  -d '{"items":[{"id":"1","timestamp":"2026-01-01"}]}'

Pull Data

curl https://your-worker/api/pull \
  -H "X-API-Token: YOUR_SECRET"

⚡ Performance Considerations

KV is eventually consistent
Optimized for read-heavy workloads
Avoid storing huge datasets

🔒 Security Best Practices

Never hardcode secrets
Validate all inputs
Restrict CORS in production
Add rate limiting (optional but recommended)

⚠️ Limitations

No relational queries
Not ideal for real-time collaboration
Needs custom user isolation logic

🔮 Possible Enhancements

👤 User-based data separation
📄 Pagination support
🔐 Data encryption
📊 Logging & monitoring
🚫 Rate limiting

🎯 Real-World Use Cases

Browser extension sync backend
Personal knowledge storage
SIEM log forwarder
Lightweight SaaS backend

🧾 Conclusion

Cloudflare Workers + KV gives you a powerful serverless backend with minimal complexity.

If you're building:

Extensions
Side projects
Edge-native apps

👉 This stack is one of the fastest ways to go live.

💬 Final Thoughts

You don’t always need Kubernetes, microservices, or a full backend stack.

Sometimes… a Worker is enough.

🔥 If you found this useful, drop a ❤️ and follow for more practical security + engineering guides.