refactor: Unified prompt composition, structured log analysis, parallel validator tracing, and intent hydration fixes

README.md

@@ -91,7 +91,7 @@ Access the application locally at `http://localhost:3000`.
 
 ### The Actor Agent
 
-Each entity takes turns through an **Actor Agent** that receives a strictly epistemically bounded prompt: its own attributes (public, plus private ones explicitly granted to itself), its subjective memory buffer, the entities co-present at its location, and the current moment. Nothing else. The actor responds with free narrative prose.
+Each entity takes turns through an **Actor Agent** that receives a strictly epistemically bounded prompt: its own attributes (public, plus private ones explicitly granted to itself), its **Cognitive Buffer**, the entities co-present at its location, and the current moment. Nothing else. The actor responds with free narrative prose.
 
 Prose is decoded into typed intents:
 
@@ -121,8 +121,8 @@ Space is a graph: `world → region → location → point of interest`, connect
 
 ### Memory Tiers
 
-- **Verbatim Buffer (implemented):** Per-character subjective event log. Every entry is stored from the owner's perspective actors resolved through the owner's alias map, outcomes attached — and recalled with naturalized time phrasing.
-- **Vector Archive (implemented):** Summarized, embedded memory entries for semantic retrieval, keeping verbatim quotes only for high-salience lines.
+- **Cognitive Buffer (implemented):** Per-character subjective event log. Every entry is stored from the owner's perspective actors resolved through the owner's alias map, outcomes attached — and recalled with naturalized time phrasing.
+- **Memory Ledger (implemented):** Summarized, embedded memory entries for semantic retrieval, keeping verbatim quotes only for high-salience lines.
 - **Dossier (planned):** Each observer's subjective beliefs about another character.
 
 Memory is per-character on purpose: recall is testimony from a vantage point, which is what makes interrogating two witnesses interesting.
@@ -156,14 +156,14 @@ The finish line for the first milestone is small on purpose. `v0` is almost on t
 - [x] Typed intent pipeline: `dialogue` / `action` / `monologue`, decoded from free prose.
 - [x] World Architect: LLM validation plus time-delta generation, end-to-end for single actions.
 - [x] Actor Agent with epistemically-bounded prompts (self, memory, co-located entities, subjective time).
-- [x] Verbatim memory buffer with per-observer subjective serialization and alias resolution.
+- [x] Verbatim Cognitive Buffer with per-observer subjective serialization and alias resolution.
 - [x] Spatial location graph (data model; perception is co-location only).
 - [x] Scenario loader (JSON → SQLite) and a playable CLI loop with human or LLM actors.
 
 **[The `v0` Milestone:](https://github.com/sortedcord/omnia-consolidated/milestone/1)**
 
 - [x] Two hand-authored NPCs live in one location, playable via CLI.
-- [x] Each has buffer and vector-archive memory and recalls something said a few turns earlier.
+- [x] Each has Cognitive Buffer and Memory Ledger memory and recalls something said a few turns earlier.
 - [x] One NPC knows a fact the other does not and, provably by testing, will not leak it.
 - [x] The Architect processes at least one non-trivial action per exchange with a visible state change.
 - [x] The whole thing persists to a SQLite file and reloads identically.
@@ -183,7 +183,7 @@ omnia/
     intent/      intent types (dialogue/action/monologue) and the prose decoder
     architect/   World Architect: LLM validation plus time-delta generation
     actor/       actor agent: epistemically-bounded prompts, pluggable prose generators
-    memory/      verbatim buffer; later the vector archive, dossier, and affect vectors
+    memory/      Cognitive Buffer; Memory Ledger (vector archive), dossier, and affect vectors
     spatial/     location and POI graph, portal-based perception
     llm/         ILLMProvider interface plus Gemini and deterministic mock implementations
     scenario/    scenario JSON schema and loader (JSON → SQLite)

apps/gui/next-env.d.ts

@@ -1,6 +1,6 @@
 /// <reference types="next" />
 /// <reference types="next/image-types/global" />
-import "./.next/types/routes.d.ts";
+import "./.next/dev/types/routes.d.ts";
 
 // NOTE: This file should not be edited
 // see https://nextjs.org/docs/app/api-reference/config/typescript for more information.

apps/gui/package.json

@@ -19,6 +19,7 @@
     "@omnia/memory": "workspace:*",
     "@omnia/scenario": "workspace:*",
     "@omnia/spatial": "workspace:*",
+    "@omnia/voice": "workspace:*",
     "@radix-ui/react-dialog": "^1.1.19",
     "@radix-ui/react-separator": "^1.1.11",
     "@radix-ui/react-slot": "^1.3.0",

apps/gui/src/components/config/ConfigView.tsx

@@ -177,13 +177,13 @@ export function ConfigView() {
                   {
                     key: "handoff",
                     label: "Memory Handoff Engine",
-                    desc: "Promotes entities' working memories to the long-term Ledger via LLM summarization and pruning.",
+                    desc: "Promotes entities' Cognitive Buffer entries to the Memory Ledger via LLM summarization and pruning.",
                     type: "generative",
                   },
                   {
                     key: "embeddings",
                     label: "Text Embeddings Generator",
-                    desc: "Generates vector embeddings for long-term memory retrieval.",
+                    desc: "Generates vector embeddings for Memory Ledger retrieval.",
                     type: "embedding",
                   },
                 ].map((task) => (

apps/gui/src/components/config/ProviderInstancesConfig.tsx

@@ -43,13 +43,7 @@ import {
   CardTitle,
   CardAction,
 } from "@/components/ui/card";
-import {
-  Item,
-  ItemContent,
-  ItemGroup,
-  ItemTitle,
-  ItemDescription,
-} from "@/components/ui/item";
+import { Item, ItemContent, ItemGroup, ItemTitle } from "@/components/ui/item";
 import { Empty, EmptyTitle, EmptyDescription } from "@/components/ui/empty";
 import { cn } from "@/lib/utils";
 import { RefreshCwIcon } from "lucide-react";
@@ -200,14 +194,12 @@ export function ProviderInstancesConfig({
         fetchModelsForExistingInstance(selectedInstanceId);
       }
     }
-    // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [selectedInstanceId, instances, availableProviders]);
 
   // Re-fetch models when provider/key/endpoint changes on new instance form
   useEffect(() => {
     if (selectedInstanceId !== "new") return;
     fetchModelsForNewInstance(editProvider, editKey, editEndpointUrl);
-    // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [editProvider, editKey, editEndpointUrl, selectedInstanceId]);
 
   const handleProviderChange = (providerId: string | null) => {

apps/gui/src/components/play/HandoffModal.tsx

@@ -0,0 +1,254 @@
+"use client";
+
+import { useState } from "react";
+import type { SimSnapshot } from "@/lib/simulation-types";
+import {
+  Dialog,
+  DialogContent,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { Badge } from "@/components/ui/badge";
+import { PromptAnalyzer } from "@/components/play/PromptAnalyzer";
+
+interface HandoffModalProps {
+  entry: SimSnapshot["log"][number];
+  onClose: () => void;
+}
+
+export function HandoffModal({ entry, onClose }: HandoffModalProps) {
+  const [activeTab, setActiveTab] = useState<"chunks" | "prompt" | "output">(
+    "chunks",
+  );
+
+  const handoffResult = entry.handoffResult;
+  const chunks = handoffResult?.chunks || [];
+
+  const getImportanceColor = (score: number) => {
+    if (score >= 8)
+      return "bg-destructive/10 text-destructive border-destructive/30";
+    if (score >= 5) return "bg-amber-500/10 text-amber-500 border-amber-500/30";
+    return "bg-emerald-500/10 text-emerald-500 border-emerald-500/30";
+  };
+
+  return (
+    <Dialog open onOpenChange={(open) => !open && onClose()}>
+      <DialogContent className="max-w-[800px] sm:max-w-[800px] h-[85vh] overflow-hidden flex flex-col p-0 gap-0 border-2">
+        <DialogHeader className="px-6 pt-5 pb-4 border-b">
+          <DialogTitle className="text-lg font-head tracking-wide text-primary flex items-center justify-between">
+            <span>Memory Handoff Details &mdash; {entry.entityName}</span>
+            {entry.usage && (
+              <span className="text-xs font-mono font-normal text-muted-foreground">
+                {entry.usage.modelName || "Handoff Model"}
+              </span>
+            )}
+          </DialogTitle>
+        </DialogHeader>
+
+        {/* Custom Tab Switcher */}
+        <div className="flex border-b bg-muted/20 px-6 py-2 gap-2">
+          <button
+            onClick={() => setActiveTab("chunks")}
+            className={`px-3 py-1.5 text-xs font-medium border transition-all duration-100 ${
+              activeTab === "chunks"
+                ? "border-primary bg-primary/10 text-primary shadow-[1px_1px_0_0_var(--primary)]"
+                : "border-transparent hover:bg-secondary text-muted-foreground"
+            }`}
+          >
+            Promoted Chunks ({chunks.length})
+          </button>
+          <button
+            onClick={() => setActiveTab("prompt")}
+            className={`px-3 py-1.5 text-xs font-medium border transition-all duration-100 ${
+              activeTab === "prompt"
+                ? "border-primary bg-primary/10 text-primary shadow-[1px_1px_0_0_var(--primary)]"
+                : "border-transparent hover:bg-secondary text-muted-foreground"
+            }`}
+          >
+            Raw LLM Prompt
+          </button>
+          <button
+            onClick={() => setActiveTab("output")}
+            className={`px-3 py-1.5 text-xs font-medium border transition-all duration-100 ${
+              activeTab === "output"
+                ? "border-primary bg-primary/10 text-primary shadow-[1px_1px_0_0_var(--primary)]"
+                : "border-transparent hover:bg-secondary text-muted-foreground"
+            }`}
+          >
+            Raw JSON Output
+          </button>
+        </div>
+
+        <div className="overflow-y-auto flex-1 p-6 space-y-4">
+          {activeTab === "chunks" && (
+            <div className="space-y-4">
+              {entry.usage && (
+                <div className="grid grid-cols-3 gap-4 border border-dotted border-border/20 p-3 bg-secondary/10 rounded text-xs font-mono">
+                  <div>
+                    <span className="text-muted-foreground block uppercase tracking-wider text-[10px]">
+                      Input Tokens
+                    </span>
+                    <strong className="text-foreground">
+                      {entry.usage.inputTokens}
+                    </strong>
+                  </div>
+                  <div>
+                    <span className="text-muted-foreground block uppercase tracking-wider text-[10px]">
+                      Output Tokens
+                    </span>
+                    <strong className="text-foreground">
+                      {entry.usage.outputTokens}
+                    </strong>
+                  </div>
+                  <div>
+                    <span className="text-muted-foreground block uppercase tracking-wider text-[10px]">
+                      Total Tokens
+                    </span>
+                    <strong className="text-foreground">
+                      {entry.usage.totalTokens}
+                    </strong>
+                  </div>
+                </div>
+              )}
+
+              {chunks.length === 0 ? (
+                <div className="border border-dotted border-border/30 p-8 text-center bg-card text-muted-foreground rounded">
+                  <p className="text-sm">
+                    No memories were promoted to the Memory Ledger during this
+                    turn.
+                  </p>
+                  <p className="text-xs mt-1">
+                    All Cognitive Buffer entries were summarized or forgotten.
+                  </p>
+                </div>
+              ) : (
+                <div className="space-y-4">
+                  <h3 className="text-xs font-semibold uppercase tracking-wider text-muted-foreground font-mono">
+                    Memory Ledger Additions
+                  </h3>
+                  {chunks.map(
+                    (
+                      chunk: { content: string; importance: number },
+                      index: number,
+                    ) => (
+                      <div
+                        key={index}
+                        className="border border-border/30 bg-card p-4 shadow-sm relative flex flex-col gap-3"
+                      >
+                        <div className="flex justify-between items-start gap-4">
+                          <div className="flex-1 text-sm text-foreground/90 leading-relaxed font-sans">
+                            {chunk.content}
+                          </div>
+                          <Badge
+                            variant="outline"
+                            className={`font-mono text-xs ${getImportanceColor(chunk.importance)}`}
+                          >
+                            Importance: {chunk.importance}
+                          </Badge>
+                        </div>
+
+                        {chunk.quotes && chunk.quotes.length > 0 && (
+                          <div className="bg-secondary/10 border-l-2 border-primary/50 p-2.5 my-1 text-xs italic text-muted-foreground space-y-1">
+                            {chunk.quotes.map((quote: string, qIdx: number) => (
+                              <div key={qIdx}>&ldquo;{quote}&rdquo;</div>
+                            ))}
+                          </div>
+                        )}
+
+                        <div className="flex flex-wrap gap-2 text-xs pt-2 border-t border-dotted border-border/10">
+                          {chunk.retainInBuffer ? (
+                            <Badge
+                              variant="outline"
+                              className="bg-primary/5 text-primary border-primary/20 text-[10px] font-mono"
+                            >
+                              Pinned in Buffer
+                            </Badge>
+                          ) : (
+                            <Badge
+                              variant="outline"
+                              className="bg-muted text-muted-foreground border-border/20 text-[10px] font-mono"
+                            >
+                              Pruned from Buffer
+                            </Badge>
+                          )}
+
+                          {chunk.involvedEntityIds &&
+                            chunk.involvedEntityIds.length > 0 && (
+                              <div className="flex items-center gap-1.5 ml-auto text-[10px] font-mono text-muted-foreground">
+                                <span>Entities:</span>
+                                {chunk.involvedEntityIds.map(
+                                  (entId: string) => (
+                                    <Badge
+                                      key={entId}
+                                      variant="outline"
+                                      className="text-[10px] px-1 py-0 border-border/20 font-mono"
+                                    >
+                                      {entId}
+                                    </Badge>
+                                  ),
+                                )}
+                              </div>
+                            )}
+                        </div>
+                      </div>
+                    ),
+                  )}
+                </div>
+              )}
+            </div>
+          )}
+
+          {activeTab === "prompt" && entry.rawPrompt && (
+            <PromptAnalyzer
+              components={
+                entry.rawPrompt.components &&
+                entry.rawPrompt.components.length > 0
+                  ? entry.rawPrompt.components
+                  : [
+                      {
+                        label: "System Prompt",
+                        type: "system",
+                        content: entry.rawPrompt.systemPrompt || "",
+                      },
+                      {
+                        label: "User Context",
+                        type: "world",
+                        content: entry.rawPrompt.userContext || "",
+                      },
+                    ]
+              }
+              inputTokens={entry.usage?.inputTokens || 0}
+              maxContext={
+                entry.usage?.maxContext !== undefined
+                  ? entry.usage.maxContext
+                  : 32768
+              }
+              modelName={entry.usage?.modelName}
+              providerInstanceName={entry.usage?.providerInstanceName}
+              outputLabel="LLM Output (Promoted Memory Chunks)"
+              outputText={
+                handoffResult
+                  ? JSON.stringify(handoffResult, null, 2)
+                  : undefined
+              }
+              outputTokens={entry.usage?.outputTokens}
+            />
+          )}
+
+          {activeTab === "output" && (
+            <div className="space-y-2 h-full flex flex-col">
+              <h4 className="text-xs font-semibold uppercase tracking-wider text-muted-foreground font-mono">
+                Raw JSON Output
+              </h4>
+              <pre className="p-3 bg-muted rounded text-xs font-mono whitespace-pre-wrap text-foreground border flex-1 overflow-y-auto max-h-[500px]">
+                {handoffResult
+                  ? JSON.stringify(handoffResult, null, 2)
+                  : "No JSON Output recorded."}
+              </pre>
+            </div>
+          )}
+        </div>
+      </DialogContent>
+    </Dialog>
+  );
+}