release: v2.0.8 - UX Persistence & Per-Agent Knowledge Mix (2026-05-14)

src/features/company/dispatcher.ts

@@ -32,9 +32,15 @@
  */
 import * as vscode from 'vscode';
 import { IAIService } from '../../core/services';
-import { logError, logInfo } from '../../utils';
+import { getActiveBrainProfile, logError, logInfo } from '../../utils';
+import { retrieveScoped, buildContextBlock } from '../../skills/scopedBrainRetriever';
+import { resolveScopeForAgent } from '../../skills/agentKnowledgeMap';
+import {
+    mapWeightToBrainFileLimit,
+    buildKnowledgeMixPolicy,
+} from '../../retrieval/knowledgeMix';
 import { getCompanyAgent } from './agents';
-import { modelForAgent, readCompanyState } from './companyConfig';
+import { modelForAgent, readCompanyState, resolveCompanyKnowledgeMix } from './companyConfig';
 import { runCeoPlanner } from './ceoPlanner';
 import { runCeoReporter } from './ceoReporter';
 import { buildSpecialistPrompt } from './promptBuilder';
@@ -86,6 +92,18 @@ export interface DispatcherDeps {
     ai: IAIService;
     /** Default model to fall back to when an agent has no override. */
     defaultModel: string;
+    /**
+     * Global Knowledge Mix weight (0–100) — fallback when an agent has no
+     * per-agent override. Mirrors `g1nation.knowledgeMix.secondBrainWeight`.
+     */
+    globalKnowledgeMixWeight: number;
+    /**
+     * Baseline number of brain files to retrieve at weight=50 (balanced).
+     * The actual count is `mapWeightToBrainFileLimit(weight, baseline)`.
+     * Pass the same value the chat path uses (`config.memoryLongTermFiles`)
+     * so company-mode behaviour stays in sync.
+     */
+    brainFileBaseline?: number;
     /**
      * Apply ConnectAI's action-tag executor to the specialist's raw response.
      * Without this hook, agent outputs containing `<create_file>` etc. would
@@ -266,10 +284,52 @@ async function _dispatchOne(
             };
         });
 
+    // ── Second Brain RAG for this specialist ────────────────────────────────
+    // The non-company chat path uses `AgentExecutor.buildMemoryContext` to
+    // pull RAG chunks before every LLM call. The dispatcher used to skip
+    // that entirely, leaving company agents *blind* to the user's stored
+    // knowledge — which made the Knowledge Mix slider effectively a no-op
+    // for company turns. We now run a lightweight scoped retrieval here so
+    // every dispatch sees the same brain the user expects, weighted by the
+    // agent's own Knowledge Mix.
+    const { weight: knowledgeWeight, source: knowledgeMixSource } =
+        resolveCompanyKnowledgeMix(state, agentId, deps.globalKnowledgeMixWeight);
+    const brainFileLimit = mapWeightToBrainFileLimit(knowledgeWeight, deps.brainFileBaseline ?? 6);
+    let brainContext = '';
+    if (brainFileLimit > 0) {
+        try {
+            const brain = getActiveBrainProfile();
+            const brainRoot = brain?.localBrainPath || '';
+            if (brainRoot) {
+                // Reuse the agent ↔ knowledge map: if the same agent name
+                // appears there (free-form .md path or canonical id), we
+                // honour its `knowledgeFolders` scope. Otherwise we search
+                // the whole brain so a missing mapping doesn't starve the
+                // dispatcher.
+                const scope = resolveScopeForAgent(agentId, brainRoot);
+                const retrieval = retrieveScoped(task, brainRoot, scope.folders, {
+                    maxResults: brainFileLimit,
+                });
+                brainContext = buildContextBlock(retrieval);
+            }
+        } catch (e: any) {
+            logError('company.dispatcher: RAG retrieval failed; continuing without brain context.', {
+                agentId, error: e?.message ?? String(e),
+            });
+        }
+    }
+    const policyBlock = buildKnowledgeMixPolicy({
+        weight: knowledgeWeight,
+        source: knowledgeMixSource,
+        agent: def.name,
+    });
+
     const system = buildSpecialistPrompt({
         agentId, state,
         agentMemory: memory, sharedDecisions: decisions,
         peerOutputs,
+        brainContext,                          // injected as `[SECOND BRAIN CONTEXT]` block
+        knowledgeMixPolicy: policyBlock,       // injected as `[KNOWLEDGE MIX POLICY]` block
     });
     const model = modelForAgent(state, agentId, deps.defaultModel);