Semantic Compression - Groups related tool calls and compresses them intelligently
Cost-Aware Pruning - Considers token pricing when deciding what to compress
Adaptive Thresholds - Learns from compression history to optimize timing
Session Persistence - Saves state across restarts
Deduplication - Removes repeated tool calls automatically
Error Purging - Cleans up failed tool call outputs after configurable turns

Installation

opencode plugin @serkanalgur/opencode-slim@latest --global

Configuration

Create ~/.config/opencode/slim.jsonc:

{
    "enabled": true,
    "compress": {
        "enabled": true,
        "permission": "allow",
        "maxContextLimit": "80%",
        "minContextLimit": "40%",
        "nudgeFrequency": 5,
        "protectUserMessages": false,
        "protectedTools": ["task", "skill", "todowrite", "todoread"]
    },
    "strategies": {
        "deduplication": {
            "enabled": true,
            "protectedTools": []
        },
        "purgeErrors": {
            "enabled": true,
            "turns": 4,
            "protectedTools": []
        }
    },
    "adaptive": {
        "enabled": true,
        "learningRate": 0.1,
        "minCompressionRatio": 0.3
    },
    "costAware": {
        "enabled": true,
        "cacheBoostFactor": 0.5
    },
    "persistence": {
        "enabled": true,
        "directory": "~/.config/opencode/slim"
    }
}

How It Works

Semantic Compression

Unlike simple text truncation, slim analyzes the semantic content of messages and groups related tool calls together. This preserves context while removing redundancy.

Cost-Aware Pruning

Slim considers the cost of tokens when deciding what to compress. It prioritizes compressing expensive operations (like large file reads) while preserving cheap but important context.

Adaptive Thresholds

The plugin learns from your compression patterns and adjusts thresholds over time. If you tend to need more context, it will compress less aggressively. If you're efficient, it will compress more.

Session Persistence

State is saved to disk, so compression history and learning persist across restarts.

Commands

/slim - Show current context stats and compression history
/slim compress - Manually trigger compression
/slim reset - Reset adaptive learning

Comparison with DCP

Feature	slim	DCP
Semantic grouping	✅	❌
Cost awareness	✅	❌
Adaptive thresholds	✅	❌
Session persistence	✅	❌
File count	~8	~150
License	MIT	AGPL-3.0
Config complexity	Low	High