Automatically reduces token usage in OpenCode by removing obsolete tool outputs from conversation history.
Add to your OpenCode config:
Using @latest ensures you always get the newest version automatically when OpenCode starts.
Restart OpenCode. The plugin will automatically start optimizing your sessions.
DCP uses two complementary techniques:
Automatic Deduplication — Silently identifies repeated tool calls (e.g., reading the same file multiple times) and keeps only the most recent output. Runs on every request with zero LLM cost.
AI Analysis — Uses a language model to semantically analyze conversation context and identify tool outputs that are no longer relevant to the current task.
When strategies.onTool is enabled, DCP exposes a prune tool to Opencode that the AI can call to trigger pruning on demand.
Adjust nudge_freq to control how aggressively the AI is prompted to prune — lower values trigger reminders sooner and more often.
Your session history is never modified. DCP replaces pruned outputs with a placeholder before sending requests to your LLM.
LLM providers like Anthropic and OpenAI cache prompts based on exact prefix matching. When DCP prunes a tool output, it changes the message content, which invalidates cached prefixes from that point forward.
Trade-off: You lose some cache read benefits but gain larger token savings from reduced context size. In most cases, the token savings outweigh the cache miss cost—especially in long sessions where context bloat becomes significant.
DCP uses its own config file (~/.config/opencode/dcp.jsonc or .opencode/dcp.jsonc), created automatically on first run.
| Option | Default | Description |
|---|---|---|
enabled |
true |
Enable/disable the plugin |
debug |
false |
Log to ~/.config/opencode/logs/dcp/ |
model |
(session) | Model for analysis (e.g., "anthropic/claude-haiku-4-5") |
showModelErrorToasts |
true |
Show notifications on model fallback |
showUpdateToasts |
true |
Show notifications when a new version is available |
strictModelSelection |
false |
Only run AI analysis with session or configured model (disables fallback models) |
pruning_summary |
"detailed" |
"off", "minimal", or "detailed" |
nudge_freq |
10 |
How often to remind AI to prune (lower = more frequent) |
protectedTools |
["task", "todowrite", "todoread", "prune", "batch", "write", "edit"] |
Tools that are never pruned |
strategies.onIdle |
["ai-analysis"] |
Strategies for automatic pruning |
strategies.onTool |
["ai-analysis"] |
Strategies when AI calls prune |
Strategies: "ai-analysis" uses LLM to identify prunable outputs. Empty array disables that trigger. Deduplication runs automatically on every request.
{
"enabled": true,
"strategies": {
"onIdle": ["ai-analysis"],
"onTool": ["ai-analysis"]
},
"protectedTools": ["task", "todowrite", "todoread", "prune", "batch", "write", "edit"]
}Settings are merged in order: Defaults → Global (~/.config/opencode/dcp.jsonc) → Project (.opencode/dcp.jsonc). Each level overrides the previous, so project settings take priority over global, which takes priority over defaults.
Restart OpenCode after making config changes.
MIT
