feat(server): add DCP clean-room context pruning

- Deduplication: removes consecutive identical tool_call+tool_result pairs
- Purge-errors: removes failed/empty tool results
- Transform orchestrator runs strategies in sequence pre-payload
- Wired into turn.ts before buildMessagesPayload
- Clean-room reimplementation (AGPL reference: behavior only)

apps/server/src/services/inference/turn.ts

@@ -21,6 +21,7 @@ import {
   buildMessagesPayload,
   loadContext,
 } from './payload.js';
+import { toDcpMessages, transformMessages, fromDcpMessages } from './dcp/index.js';
 import {
   finalizeCompletion,
   finalizeEmpty,
@@ -156,9 +157,20 @@ export async function runAssistantTurn(
       ctx.log.warn({ sessionId }, 'inference: session or project missing mid-loop');
       break;
     }
-    const { session: iterSession, project: iterProject, history } = loaded;
+    let { session: iterSession, project: iterProject, history } = loaded;
     const projectRoot = await resolveProjectRoot(iterProject.path);
 
+    try {
+      const dcpMsgs = toDcpMessages(history);
+      const { messages: pruned, stats } = transformMessages(chatId, dcpMsgs);
+      if (stats.removedCount > 0) {
+        ctx.log.info({ chatId, ...stats }, 'dcp: transform removed messages');
+        history = fromDcpMessages(pruned) as typeof history;
+      }
+    } catch (err) {
+      ctx.log.warn({ err: err instanceof Error ? err.message : String(err), chatId }, 'dcp: transform skipped');
+    }
+
     // v1.14.0: log step boundary for instrumentation. step_start parts are in
     // the schema CHECK but not emitted here — writing to the assistant message
     // before the stream phase creates a sequence-0 collision with