diff --git a/README.md b/README.md
index 330d7fc..d92b849 100644
--- a/README.md
+++ b/README.md
@@ -186,7 +186,7 @@ console.log(chunks);
 
 // Manually compile history into memories at end of conversation
 // Happens automatically when coverstaions are compressed
-await ai.language.updateMemory(history, memory);
+await ai.language.memorize(history, memory);
 
 // Summarize text
 const summary = await ai.language.summarize(longText, 200);
diff --git a/package.json b/package.json
index 6d39719..201b0b7 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@ztimson/ai-utils",
-	"version": "1.4.4",
+	"version": "1.4.5",
 	"description": "AI Utility library",
 	"author": "Zak Timson",
 	"license": "MIT",
diff --git a/src/helpers.ts b/src/helpers.ts
index 29d128d..b38992d 100644
--- a/src/helpers.ts
+++ b/src/helpers.ts
@@ -7,10 +7,24 @@ export type MemoryNode = {
 	backlinks: string[];
 }
 
-export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
+export function extractLinks(content: string): string[] {
+	if (!content) return [];
+	const matches = content.matchAll(/\[\[([^\]|]+)(?:\|[^\]]*)?\]\]/g);
+	return [...new Set([...matches].map(m => m[1].trim()))];
+}
+
+export function rebuildGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
 	const mems = memories instanceof MemoryCache ? memories.memories : memories;
 	const nameSet = new Set(mems.map(m => m.name));
-	const ghosts = new Set<string>();
+
+	for (const m of mems) m.links = extractLinks(m.content).filter(l => l !== m.name);
+	for (const m of mems) m.backlinks = [];
+	for (const m of mems) {
+		for (const link of m.links) {
+			const target = mems.find(t => t.name === link);
+			if (target) target.backlinks.push(m.name);
+		}
+	}
 
 	const nodes: MemoryNode[] = mems.map(m => ({
 		name: m.name,
@@ -19,6 +33,7 @@ export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[]
 		backlinks: m.backlinks,
 	}));
 
+	const ghosts = new Set<string>();
 	for (const node of nodes) {
 		for (const link of node.links) {
 			if (!nameSet.has(link)) ghosts.add(link);
@@ -31,30 +46,28 @@ export function buildMemoryGraph(memories: Memory[] | MemoryCache): MemoryNode[]
 			name,
 			missing: true,
 			links: [],
-			backlinks: nodes
-				.filter(n => n.links.includes(name))
-				.map(n => n.name),
-		}))
+			backlinks: nodes.filter(n => n.links.includes(name)).map(n => n.name),
+		})),
 	];
 }
 
-export function renderMemoryGraph(nodes) {
+export function renderMemoryGraph(nodes: MemoryNode[]): string {
 	if (!nodes.length) return 'No memories yet.';
 
-	const groups = new Map();
+	const groups = new Map<string, (MemoryNode & {label: string})[]>();
 	for (const node of nodes) {
 		const [prefix, ...rest] = node.name.split('/');
 		const group = rest.length ? prefix : 'Root';
 		const label = rest.length ? rest.join('/') : node.name;
 		if (!groups.has(group)) groups.set(group, []);
-		groups.get(group).push({...node, label});
+		groups.get(group)!.push({...node, label});
 	}
 
 	const ghostCount = nodes.filter(n => n.missing).length;
 	const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
 
 	for (const group of [...groups.keys()].sort()) {
-		const items = groups.get(group).sort((a, b) => a.label.localeCompare(b.label));
+		const items = groups.get(group)!.sort((a, b) => a.label.localeCompare(b.label));
 		lines.push(`${group}/`);
 		items.forEach((n, i) => {
 			const last = i === items.length - 1;
diff --git a/src/kd-tree.ts b/src/kd-tree.ts
index db32ec2..dd43378 100644
--- a/src/kd-tree.ts
+++ b/src/kd-tree.ts
@@ -103,9 +103,10 @@ class BoundedMaxHeap<T> {
 export class KDTree<T = unknown> {
 	private root: KDNode<T> | null = null;
 	private _size = 0;
-	private readonly dims: number;
 	private readonly distanceFn: (a: number[], b: number[]) => number;
 
+	readonly dims: number;
+
 	/**
 	 * @param dims           Dimensionality of all vectors (must be consistent).
 	 * @param metric         Distance metric to use. Default: "euclidean".
diff --git a/src/llm.ts b/src/llm.ts
index 1ed9fd8..8459eb9 100644
--- a/src/llm.ts
+++ b/src/llm.ts
@@ -1,4 +1,4 @@
-import {snakeCase} from '@ztimson/utils';
+import {clean, snakeCase} from '@ztimson/utils';
 import {AbortablePromise, Ai} from './ai.ts';
 import {Anthropic} from './antrhopic.ts';
 import {OpenAi} from './open-ai.ts';
@@ -132,7 +132,7 @@ class LLM {
 			return {
 				name: toolName,
 				description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
-				args: <any>({
+				args: clean<any>({
 					context: !a.delegate ? {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true} : undefined,
 					instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
 				}),
@@ -143,8 +143,6 @@ class LLM {
 						.map(name => allAgents.find(x => x.name === name))
 						.filter((x): x is Agent => !!x && x.name !== a.name);
 
-					// Delegate continues the SAME live conversation - no new user turn needed,
-					// `history` is always current (shared, mutated in place) by the time this runs
 					const q = a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`;
 
 					const request = this.ask(q, {
@@ -218,7 +216,7 @@ ${a.system}`,
 		if(!skills?.length) return {prompt: '', tools: []};
 		const list = skills.map(s => `- ${s.name}: ${s.description}`).join('\n');
 		return {
-			prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
+			prompt: `You have access to the following skill documents, whenever there is overlap between a question and a skill file, use \`skill_read\` to get instructions and background knowledge:\n${list}`,
 			tools: [{
 				name: 'skill_read',
 				description: 'Read the full content of a skill/knowledge document',
@@ -318,19 +316,30 @@ ${a.system}`,
 							} else listed.push(r);
 						}
 
-						prompts.unshift(`You have access to the following memory files:
-${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
+						prompts.unshift(`You have a background memory process which has prefetched relevant information${mem.update ? ' and will create new memories from this conversation' : ''} for you
+Assume it is perfect and never mention this process to anyone ever
+Always use your memories to craft a personalized response, they contain links / [[wiki links]] which you use navigate between them
+${mem.tool ? `You can access memory files via the \`memory_search\` and \`memory_recall\` tools
+When you need information about the user, \`memory_recall\` \`People/User\` before asking (fetch if not included bellow)
+When you need information not provided, attempt 1-3 \`memory_search\` calls with unique queries before asking` : ''}
+
 ${preloaded.length ? `
-Relevant memories have been preloaded:
-${preloaded.map(r => `
-**${r.name}**
-${r.description}
+Prefetched Memories (Most relevant first):
+
+${preloaded.map(r => `Memory: ${r.name}
+Description: ${r.description}
+Linked: ${[r.links, ...r.backlinks].join(', ')}
+\`\`\`
 ${r.content}
-`).join('\n---\n')}
-` : ''}${listed.length ? `
-Additional relevant memories (use \`memory_recall\`):
-${listed.map(r => r.name).join(', ')}
-` : ''}`.trim());
+\`\`\``).join('\n\n')}` : ''}
+
+${mem.tool && listed.length ? listed.map(r => `Memory: ${r.name}
+Description: ${r.description}
+Linked: ${[r.links, ...r.backlinks].join(', ')}
+<!-- Truncated -->`).join('\n\n') : ''}
+
+${mem.tool ? `Full memory list:
+${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}` : ''}`.trim())
 					}
 					if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
 				}
@@ -374,14 +383,6 @@ ${listed.map(r => r.name).join(', ')}
 		return Object.assign(promise, {abort});
 	}
 
-	/**
-	 * Digest full conversation history into memory documents.
-	 * Call on session end to persist the conversation.
-	 */
-	async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
-		return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
-	}
-
 	/**
 	 * Compress chat history to reduce context size
 	 * @param {LLMMessage[]} history Chatlog that will be compressed
@@ -561,6 +562,14 @@ ${listed.map(r => r.name).join(', ')}
 		};
 	}
 
+	/**
+	 * Digest full conversation history into memory documents.
+	 * Call on session end to persist the conversation.
+	 */
+	async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
+		return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
+	}
+
 	/**
 	 * Create a summary of some text
 	 * @param {string} text Text to summarize
diff --git a/src/memory.ts b/src/memory.ts
index bc146c0..96c3d53 100644
--- a/src/memory.ts
+++ b/src/memory.ts
@@ -1,3 +1,4 @@
+import {MemoryNode, rebuildGraph} from './helpers.ts';
 import {LLMRequest, LLMMessage} from './llm.ts';
 import {AiTool} from './tools.ts';
 import {KDPoint, KDTree} from './kd-tree.ts';
@@ -12,79 +13,6 @@ const GENERIC_TEMPLATE = `# {{Title}}
 
 ## Related`;
 
-export class MemoryCache {
-	private tree: KDTree<MemoryRef>;
-	public memories: Memory[];
-
-	get length() { return this.memories.length; }
-
-	constructor(memories: Memory[]) {
-		this.memories = memories;
-		this.tree = this.buildTree();
-	}
-
-	private buildTree(): KDTree<MemoryRef> {
-		const embedded = this.memories.filter(m => m.embedding?.length);
-		if (!embedded.length) return new KDTree<MemoryRef>(0);
-
-		const dims = embedded[0].embedding.length;
-		const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
-			vector: m.embedding,
-			payload: {name: m.name, description: m.description},
-		}));
-
-		return new KDTree<MemoryRef>(dims, 'cosine', points);
-	}
-
-	search(query: number[], limit: number): MemoryRef[] {
-		const results = this.tree.knn(query, limit);
-		return results.map(r => r.point.payload);
-	}
-
-	add(memory: Memory): void {
-		this.memories.push(memory);
-		rebuildGraph(this.memories);
-		this.rebuild();
-	}
-
-	update(memory: Memory): void {
-		const idx = this.memories.findIndex(m => m.name === memory.name);
-		if (idx !== -1) {
-			this.memories[idx] = memory;
-		} else {
-			this.memories.push(memory);
-		}
-		rebuildGraph(this.memories);
-		this.rebuild();
-	}
-
-	remove(name: string): void {
-		const idx = this.memories.findIndex(m => m.name === name);
-		if (idx !== -1) {
-			this.memories.splice(idx, 1);
-			rebuildGraph(this.memories);
-			this.rebuild();
-		}
-	}
-
-	rebuild(): void {
-		this.tree = this.buildTree();
-	}
-}
-
-export type MemoryOptions = {
-	/** Memory object */
-	memory: Memory[] | MemoryCache;
-	/** Inject N memories into the system prompt */
-	inject?: boolean;
-	/** expose recall tool to LLM */
-	tool?: boolean;
-	/** Update memory on compression */
-	update?: boolean;
-	/** Max context size of memories to inject to each call (removed immediately after use) */
-	maxTokens?: number;
-}
-
 export type Memory = {
 	name: string;
 	description: string;
@@ -104,23 +32,6 @@ type FactBucket = {
 	facts: string[];
 }
 
-function extractLinks(content: string): string[] {
-	if (!content) return [];
-	const matches = content.matchAll(/\[\[([^\]]+)\]\]/g);
-	return [...new Set([...matches].map(m => m[1].trim()))];
-}
-
-export function rebuildGraph(memories: Memory[]): void {
-	for (const m of memories) m.links = extractLinks(m.content).filter(l => l !== m.name);
-	for (const m of memories) m.backlinks = [];
-	for (const m of memories) {
-		for (const link of m.links) {
-			const target = memories.find(t => t.name === link);
-			if (target) target.backlinks.push(m.name);
-		}
-	}
-}
-
 function dedupeFacts(facts: string[]): string[] {
 	const seen = new Map<string, string>();
 	for (const f of facts) {
@@ -141,12 +52,132 @@ function cosineDistance(a: number[], b: number[]): number {
 	return denom === 0 ? 1 : 1 - dot / denom;
 }
 
-function getWeekMonday(date: Date = new Date()): string {
-	const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
-	const day = d.getUTCDay();
-	const diff = day === 0 ? -6 : 1 - day;
-	d.setUTCDate(d.getUTCDate() + diff);
-	return d.toISOString().slice(0, 10);
+function cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
+	return memories
+		.filter(m => m.embedding?.length)
+		.map(m => ({ref: {name: m.name, description: m.description}, distance: cosineDistance(query, m.embedding)}))
+		.sort((a, b) => a.distance - b.distance)
+		.slice(0, limit)
+		.map(s => s.ref);
+}
+
+export class MemoryCache {
+	private tree!: KDTree<MemoryRef>;
+	public memories: Memory[];
+	public nodes: MemoryNode[] = [];
+
+	get length() { return this.memories.length; }
+
+	constructor(memories: Memory[]) {
+		this.memories = memories;
+		this.rebuild();
+	}
+
+	private buildTree(): KDTree<MemoryRef> {
+		const embedded = this.memories.filter(m => m.embedding?.length);
+		if (!embedded.length) return new KDTree<MemoryRef>(0);
+
+		const dims = embedded[0].embedding.length;
+		const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
+			vector: m.embedding,
+			payload: {name: m.name, description: m.description},
+		}));
+
+		return new KDTree<MemoryRef>(dims, 'cosine', points);
+	}
+
+	search(query: number[], limit: number): MemoryRef[] {
+		if (!this.tree || this.tree.dims === 0) return [];
+		return this.tree.knn(query, limit).map(r => r.point.payload);
+	}
+
+	add(memory: Memory): void {
+		this.memories.push(memory);
+		this.rebuild();
+	}
+
+	update(memory: Memory): void {
+		const idx = this.memories.findIndex(m => m.name === memory.name);
+		if (idx !== -1) this.memories[idx] = memory;
+		else this.memories.push(memory);
+		this.rebuild();
+	}
+
+	remove(name: string): void {
+		const idx = this.memories.findIndex(m => m.name === name);
+		if (idx !== -1) {
+			this.memories.splice(idx, 1);
+			this.rebuild();
+		}
+	}
+
+	rebuild(): void {
+		this.nodes = rebuildGraph(this.memories);
+		this.tree = this.buildTree();
+	}
+}
+
+class MemoryAccessor {
+	readonly list: Memory[];
+	private readonly cache: MemoryCache | null;
+
+	constructor(memories: Memory[] | MemoryCache) {
+		this.cache = memories instanceof MemoryCache ? memories : null;
+		this.list = this.cache ? this.cache.memories : <Memory[]>memories;
+	}
+
+	find(name: string): Memory | undefined {
+		return this.list.find(m => m.name === name);
+	}
+
+	commit(): MemoryNode[] {
+		if (this.cache) {
+			this.cache.rebuild();
+			return this.cache.nodes;
+		}
+		return rebuildGraph(this.list);
+	}
+
+	ghosts(): string[] {
+		const nodes = this.cache ? this.cache.nodes : rebuildGraph(this.list);
+		return nodes.filter(n => n.missing).map(n => n.name);
+	}
+
+	search(vector: number[], limit: number): MemoryRef[] {
+		return this.cache ? this.cache.search(vector, limit) : cosineSearch(vector, this.list, limit);
+	}
+
+	forget(name: string): boolean {
+		const idx = this.list.findIndex(m => m.name === name);
+		if (idx === -1) return false;
+		this.list.splice(idx, 1);
+		this.commit();
+		return true;
+	}
+
+	async backfillEmbeddings(llm: any): Promise<number> {
+		const missing = this.list.filter(m => !m.embedding?.length);
+		if (!missing.length) return 0;
+		await Promise.all(missing.map(async node => {
+			const [e] = await llm.embedding(node.content);
+			if (e) node.embedding = e.embedding;
+		}));
+		this.commit();
+		return missing.length;
+	}
+}
+
+export type MemoryOptions = {
+	/** Memory object */
+	memory: Memory[] | MemoryCache;
+	/** Inject N memories into the system prompt */
+	inject?: boolean;
+	/** expose recall tool to LLM */
+	tool?: boolean;
+	/** Update memory on compression */
+	update?: boolean;
+	/** Max context size of memories to inject to each call (removed immediately after use) */
+	maxTokens?: number;
 }
 
 export class MemoryManager {
@@ -159,21 +190,6 @@ export class MemoryManager {
 	}>();
 
 	tools = {
-		read: (memories: Memory[] | MemoryCache): AiTool => ({
-			name: 'memory_recall',
-			description: 'Read the full content of a memory document',
-			args: {
-				name: {type: 'string', description: 'Exact memory name', required: true},
-			},
-			fn: (args: any) => {
-				const mems = this.unwrap(memories);
-				const mem = mems.find(m => m.name === args.name);
-				if (!mem) return 'Document not found';
-				this.touch(mem.name);
-				return mem.content;
-			},
-		}),
-
 		forget: (memories: Memory[] | MemoryCache): AiTool => ({
 			name: 'memory_forget',
 			description: 'Permanently delete a memory document and clean up all references to it',
@@ -185,68 +201,50 @@ export class MemoryManager {
 				return result ? `Forgotten: ${args.name}` : `Not found: ${args.name}`;
 			},
 		}),
+
+		read: (memories: Memory[] | MemoryCache): AiTool => ({
+			name: 'memory_recall',
+			description: 'Read the full content of a memory document',
+			args: {
+				name: {type: 'string', description: 'Exact memory name', required: true},
+			},
+			fn: (args: any) => {
+				const mem = this.access(memories).find(args.name);
+				if (!mem) return 'Document not found';
+				this.touch(mem.name);
+				return mem.content;
+			},
+		}),
+
+		search: (memories: Memory[] | MemoryCache): AiTool => ({
+			name: 'memory_search',
+			description: 'Use embeddings to find the MOST relevant memories, even if NOT relevant',
+			args: {
+				query: {type: 'string', description: 'What to look for in the memories', required: true},
+				limit: {type: 'number', description: 'Number of memories to return', default: 1},
+			},
+			fn: async ({query, limit}) => {
+				const mem = await this.recollect(query, memories, limit)
+				return mem.map(m => `Memory: ${m.name}
+Description: ${m.description}
+Links: ${[...m.links, ...m.backlinks].join(', ')}
+\`\`\`
+${m.content}
+\`\`\``).join('\n\n');
+			},
+		}),
 	};
 
 	constructor(private llm: any) {}
 
-	private ghostNodes(memories: Memory[]): string[] {
-		const names = new Set(memories.map(m => m.name));
-		const ghosts = new Set<string>();
-		for (const m of memories) {
-			for (const link of m.links) {
-				if (!names.has(link)) ghosts.add(link);
-			}
-		}
-		return [...ghosts];
-	}
-
 	static normalize(m?: Memory[] | MemoryCache | MemoryOptions) {
-		if(!m) return null;
+		if (!m) return null;
 		const raw = m instanceof MemoryCache || Array.isArray(m);
 		return raw ? {memory: <Memory[] | MemoryCache>m, inject: true, tool: true, update: true} : {inject: true, tool: true, update: true, ...m};
 	}
 
-	private unwrap(memories: Memory[] | MemoryCache): Memory[] {
-		return memories instanceof MemoryCache ? memories.memories : memories;
-	}
-
-	private sync(memories: Memory[] | MemoryCache): void {
-		if (memories instanceof MemoryCache) memories.rebuild();
-	}
-
-	private parseFrontmatter(content: string): {fm: Map<string, string>, body: string} {
-		const match = content.match(/^---\n([\s\S]*?)\n---\n?([\s\S]*)$/);
-		if (!match) return {fm: new Map(), body: content};
-		const fm = new Map<string, string>();
-		for (const line of match[1].split('\n')) {
-			const i = line.indexOf(':');
-			if (i === -1) continue;
-			fm.set(line.slice(0, i).trim(), line.slice(i + 1).trim());
-		}
-		return {fm, body: match[2]};
-	}
-
-	private writeFrontmatter(fm: Map<string, string>, body: string): string {
-		const lines = [...fm.entries()].map(([k, v]) => `${k}: ${v}`);
-		return `---\n${lines.join('\n')}\n---\n\n${body.trimStart()}`;
-	}
-
-	private stripHeader(content: string): string {
-		return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
-	}
-
-	private touchHeader(node: Memory, body: string): string {
-		const {fm} = this.parseFrontmatter(node.content);
-		fm.set('name', node.name);
-		fm.set('description', node.description || '');
-		fm.set('modified', new Date().toISOString());
-		return this.writeFrontmatter(fm, body);
-	}
-
-	private ensureDoc(node: Memory): void {
-		if (node.content) return;
-		const title = node.name.split('/').pop() ?? node.name;
-		node.content = this.touchHeader(node, `# ${title}\n`);
+	private access(memories: Memory[] | MemoryCache): MemoryAccessor {
+		return new MemoryAccessor(memories);
 	}
 
 	private appendFacts(node: Memory, facts: string[]): void {
@@ -260,137 +258,78 @@ export class MemoryManager {
 		node.content = this.touchHeader(node, newBody);
 	}
 
-	decay() {
-		for(const [name, ttl] of this.recentlyTouched) {
-			if(ttl <= 1) this.recentlyTouched.delete(name);
-			else this.recentlyTouched.set(name, ttl - 1);
-		}
+	private ensureDoc(node: Memory): void {
+		if (node.content) return;
+		const title = node.name.split('/').pop() ?? node.name;
+		node.content = this.touchHeader(node, `# ${title}\n`);
 	}
 
-	touch(name: string, ttl = 2) {
-		this.recentlyTouched.set(name, ttl);
-	}
+	private async factAgent(conversation: string, store: MemoryAccessor, options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
+		const ghosts = store.ghosts();
 
-	getTouched(): string[] {
-		return [...this.recentlyTouched.keys()];
-	}
+		const response = await this.llm.ask(conversation, {
+			model: options.model,
+			temperature: 0.2,
+			system: `You are a fact extractor to build obsidian knowledge vaults.
+Analyze this conversation and extract facts worth remembering long-term.
 
-	forget(name: string, memories: Memory[] | MemoryCache): boolean {
-		const mem = this.unwrap(memories);
-		const idx = mem.findIndex(m => m.name === name);
-		if (idx === -1) return false;
+Rules:
+- Always extract facts that the user explicitly told you to remember
+- ONLY extract current facts the USER explicitly stated about themselves, their work, projects or decisions that were MADE during this conversation
+- DO NOT extract greetings, pleasantries, or generic exchanges
+- DO NOT extract deltas or changes in facts; ONLY the end fact
+- DO NOT extract anything the AI/assistant itself said
+- If nothing worth remembering was said, return an empty buckets array
 
-		mem.splice(idx, 1);
-		rebuildGraph(mem);
-		this.sync(memories);
-		return true;
-	}
+When extracting facts, you MUST also decide the exact destination path:
+- Reuse node names (including ghost) as much as possible IF the facts belongs there
+- All information primarily about the user should go under "People/User"
+- When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide) — you are not limited to any fixed list of collections, use whatever fits
+- For journal entries, use "Journal"
 
-	async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
-		const mem = this.unwrap(memories);
-		if (!mem.length) return [];
+Available nodes:
+- Journal
+${this.listNodes(store.list).filter(n => !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}
+${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
+			schema: {
+				buckets: {type: 'array', description: 'Groups of facts to remember, each assigned to a different node. Return an empty array if there is nothing worth storing in an obsidian vault', items: {
+					type: 'object', items: {
+							subject: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide"), or "Journal"', required: true},
+							facts: {
+								type: 'array',
+								description: 'Facts to store at this destination',
+								items: {type: 'string', description: 'A single fact'},
+							},
+						},
+					},
+				},
+			},
+		});
 
-		const [e] = await this.llm.embedding(query);
-		if (!e) return [];
-
-		let vectorResults: MemoryRef[];
-		if (memories instanceof MemoryCache) vectorResults = memories.search(e.embedding, limit);
-		else vectorResults = this.cosineSearch(e.embedding, mem, limit);
-		const found = new Set<string>(vectorResults.map(r => r.name));
-
-		if (graphDepth > 0) {
-			const frontier = [...found];
-			for (let depth = 0; depth < graphDepth; depth++) {
-				const next: string[] = [];
-				for (const name of frontier) {
-					const node = mem.find(m => m.name === name);
-					if (!node) continue;
-					for (const link of node.links) {
-						if (!found.has(link) && mem.find(m => m.name === link)) {
-							found.add(link);
-							next.push(link);
-						}
-					}
-				}
-				frontier.splice(0, frontier.length, ...next);
-				if (!frontier.length) break;
-			}
+		const buckets = new Map<string, string[]>();
+		for(const bucket of response.buckets ?? []) {
+			const subject = bucket.subject.trim().toLowerCase() === 'journal'
+				? `Journal/${weekKey}` : bucket.subject.trim();
+			const facts = buckets.get(subject) ?? [];
+			facts.push(...dedupeFacts(bucket.facts));
+			buckets.set(subject, facts);
 		}
 
-		const vectorOrder = vectorResults.map(r => r.name);
-		const graphExpansions = [...found].filter(n => !vectorOrder.includes(n));
-		const ordered = [...vectorOrder, ...graphExpansions];
-		return ordered.map(n => mem.find(m => m.name === n)!).filter(Boolean);
+		return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
 	}
 
-	private cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
-		const scored = memories
-			.filter(m => m.embedding?.length)
-			.map(m => ({
-				ref: {name: m.name, description: m.description},
-				distance: cosineDistance(query, m.embedding),
-			}))
-			.sort((a, b) => a.distance - b.distance)
-			.slice(0, limit);
-		return scored.map(s => s.ref);
+	private getWeekMonday(date: Date = new Date()): string {
+		const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
+		const day = d.getUTCDay();
+		const diff = day === 0 ? -6 : 1 - day;
+		d.setUTCDate(d.getUTCDate() + diff);
+		return d.toISOString().slice(0, 10);
 	}
 
 	private listNodes(memories: Memory[]): MemoryRef[] {
 		return memories.map(m => ({name: m.name, description: m.description}));
 	}
 
-	async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
-		const conversation = history
-			.filter(h => h.role === 'user' || h.role === 'assistant')
-			.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
-		if (!conversation) return [];
-
-		const uid = `${Date.now()}_${Math.random().toString(36).slice(2)}`;
-		// NOTE: adjust field names below (id/tool_call_id/name) to match your LLMMessage/tool-call schema.
-		const pending = {role: 'tool', name: 'memory_process', id: uid, content: 'Processing…'} as unknown as LLMMessage;
-		history.push(pending);
-
-		const mem = this.unwrap(memories);
-		const buckets = await this.factAgent(conversation, mem, options, getWeekMonday());
-		const touched: Memory[] = [];
-
-		for (const {subject, facts} of buckets) {
-			let node = mem.find(m => m.name === subject);
-			if (!node) {
-				node = {name: subject, description: '', content: '', embedding: [], links: [], backlinks: []};
-				mem.push(node);
-			}
-			this.appendFacts(node, facts);
-			const [e] = await this.llm.embedding(node.content);
-			if (e) node.embedding = e.embedding;
-			this.touch(node.name);
-			touched.push(node);
-		}
-
-		if (touched.length) {
-			rebuildGraph(mem);
-			this.sync(memories);
-			(pending as any).content = `Saved to ${touched.map(n => `[[${n.name}]]`).join(', ')}`;
-			for (const node of touched) this.reconcile(node, memories, options).catch(() => {});
-		} else {
-			(pending as any).content = 'Nothing worth remembering.';
-		}
-
-		return touched;
-	}
-
-	/** Manual/cron entry point. scope 'touched' only reconciles docs with a pending Facts inbox. */
-	async reconcileVault(memories: Memory[] | MemoryCache, options: LLMRequest, scope: 'touched' | 'all' = 'touched'): Promise<void> {
-		const mem = this.unwrap(memories);
-		const targets = scope === 'all' ? mem : mem.filter(m => m.content.includes(FACTS_HEADING));
-		await Promise.all(targets.map(node => this.reconcile(node, memories, options)));
-		this.sync(memories);
-	}
-
-	/**
-	 * Coalescing queue: if a doc is already reconciling, mark it dirty and abort the in-flight
-	 * request. The loop below always re-reads node.content fresh, so nothing is ever dropped.
-	 */
 	private reconcile(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
 		const key = node.name;
 		const existing = this.queues.get(key);
@@ -402,21 +341,20 @@ export class MemoryManager {
 
 		const entry = {dirty: false, request: null, task: Promise.resolve()};
 		this.queues.set(key, entry);
-		const mem = this.unwrap(memories);
+		const store = this.access(memories);
 		entry.task = (async () => {
 			do {
 				entry.dirty = false;
-				await this.reconcileDoc(node, mem, options, entry);
+				await this.docAgent(node, store.list, options, entry);
 			} while (entry.dirty);
 		})().finally(() => {
 			this.queues.delete(key);
-			rebuildGraph(mem);
-			this.sync(memories);
+			store.commit();
 		});
 		return entry.task;
 	}
 
-	private async reconcileDoc(node: Memory, memories: Memory[], options: LLMRequest, entry: {request: {abort?: () => void} | null}): Promise<void> {
+	private async docAgent(node: Memory, memories: Memory[], options: LLMRequest, entry: {request: {abort?: () => void} | null}): Promise<void> {
 		const currentBody = this.stripHeader(node.content);
 		let update;
 		try {
@@ -470,50 +408,128 @@ ${currentBody}
 		if (e) node.embedding = e.embedding;
 	}
 
-	private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
-		const buckets = new Map<string, string[]>();
-		const ghosts = this.ghostNodes(memories);
+	private parseFrontmatter(content: string): {fm: Map<string, string>, body: string} {
+		const match = content.match(/^---\n([\s\S]*?)\n---\n?([\s\S]*)$/);
+		if (!match) return {fm: new Map(), body: content};
+		const fm = new Map<string, string>();
+		for (const line of match[1].split('\n')) {
+			const i = line.indexOf(':');
+			if (i === -1) continue;
+			fm.set(line.slice(0, i).trim(), line.slice(i + 1).trim());
+		}
+		return {fm, body: match[2]};
+	}
 
-		await this.llm.ask(conversation, {
-			model: options.model,
-			temperature: 0.2,
-			system: `You are a fact extractor. Analyze this conversation and extract facts worth remembering long-term.
+	private stripHeader(content: string): string {
+		return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
+	}
 
-Rules:
-- ONLY extract current facts the USER explicitly stated about themselves, their work, or their projects
-- ONLY extract decisions that were MADE during this conversation
-- DO NOT extract anything the AI said, its capabilities, or meta-conversation about the AI
-- DO NOT extract greetings, pleasantries, or generic exchanges
-- DO NOT extract deltas or changes in facts; ONLY the end fact
-- If nothing worth remembering was said, do not call any tools
+	private touchHeader(node: Memory, body: string): string {
+		const {fm} = this.parseFrontmatter(node.content);
+		fm.set('name', node.name);
+		fm.set('description', node.description || '');
+		fm.set('modified', new Date().toISOString());
+		return this.writeFrontmatter(fm, body);
+	}
 
-When extracting facts, you MUST also decide the exact destination path:
-- Reuse node names (including ghost) as much as possible IF the facts belongs there
-- All information primarily about the user should go under "People/User"
-- When required, create a new path following collection/subject format (e.g., People/Sarah, Projects/Oxide) — you are not limited to any fixed list of collections, use whatever fits
-- For journal entries, use "Journal"
+	private writeFrontmatter(fm: Map<string, string>, body: string): string {
+		const lines = [...fm.entries()].map(([k, v]) => `${k}: ${v}`);
+		return `---\n${lines.join('\n')}\n---\n\n${body.trimStart()}`;
+	}
 
-Available nodes:
-- Journal
-${this.listNodes(memories).filter(n => !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}
-${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
-			tools: [{
-				name: 'facts_extract',
-				description: 'Submit facts with their destination',
-				args: {
-					destination: {type: 'string', description: 'Exact existing node name OR new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
-					facts: {type: 'string', description: 'Comma-separated facts', required: true},
-				},
-				fn: (args: any) => {
-					const subject = args.destination.trim().toLowerCase() === 'journal'
-						? `Journal/${weekKey}` : args.destination.trim();
-					const facts = buckets.get(subject) ?? [];
-					facts.push(...dedupeFacts(String(args.facts).split(',')));
-					buckets.set(subject, facts);
-					return 'Recorded';
-				},
-			}],
-		});
-		return buckets.entries().toArray().map(([subject, facts]) => ({subject, facts}));
+	decay() {
+		for (const [name, ttl] of this.recentlyTouched) {
+			if (ttl <= 1) this.recentlyTouched.delete(name);
+			else this.recentlyTouched.set(name, ttl - 1);
+		}
+	}
+
+	touch(name: string, ttl = 2) {
+		this.recentlyTouched.set(name, ttl);
+	}
+
+	forget(name: string, memories: Memory[] | MemoryCache): boolean {
+		return this.access(memories).forget(name);
+	}
+
+	async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
+		const store = this.access(memories);
+		if (!store.list.length) return [];
+
+		await store.backfillEmbeddings(this.llm);
+
+		const [e] = await this.llm.embedding(query);
+		if (!e) return [];
+
+		const vectorResults = store.search(e.embedding, limit);
+		const found = new Set<string>(vectorResults.map(r => r.name));
+
+		if (graphDepth > 0) {
+			let frontier = [...found];
+			for (let depth = 0; depth < graphDepth && frontier.length; depth++) {
+				const next: string[] = [];
+				for (const name of frontier) {
+					const node = store.find(name);
+					if (!node) continue;
+					for (const link of node.links) {
+						if (!found.has(link) && store.find(link)) {
+							found.add(link);
+							next.push(link);
+						}
+					}
+				}
+				frontier = next;
+			}
+		}
+
+		const vectorOrder = vectorResults.map(r => r.name);
+		const graphExpansions = [...found].filter(n => !vectorOrder.includes(n));
+		return [...vectorOrder, ...graphExpansions].map(n => store.find(n)!).filter(Boolean);
+	}
+
+	async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
+		const conversation = history
+			.filter(h => h.role === 'user' || h.role === 'assistant')
+			.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
+		if (!conversation) return [];
+
+		const uid = `${Date.now()}_${Math.random().toString(36).slice(2)}`;
+		const pending = {role: 'tool', name: 'memory_process', id: uid, content: conversation} as unknown as LLMMessage;
+		history.push(pending);
+
+		const store = this.access(memories);
+		const buckets = await this.factAgent(conversation, store, options, this.getWeekMonday());
+		const touched: Memory[] = [];
+
+		for (const {subject, facts} of buckets) {
+			let node = store.find(subject);
+			if (!node) {
+				node = {name: subject, description: '', content: '', embedding: [], links: [], backlinks: []};
+				store.list.push(node);
+			}
+			this.appendFacts(node, facts);
+			const [e] = await this.llm.embedding(node.content);
+			if (e) node.embedding = e.embedding;
+			this.touch(node.name);
+			touched.push(node);
+		}
+
+		if (touched.length) {
+			store.commit();
+			(pending as any).content = `Saved to ${touched.map(n => `[[${n.name}]]`).join(', ')}`;
+			await Promise.all(touched.map(node => this.reconcile(node, memories, options).catch(() => {})));
+		} else {
+			(pending as any).content = 'Nothing worth remembering.';
+		}
+
+		(touched as any).uid = uid;
+		return touched;
+	}
+
+	async reconcileVault(memories: Memory[] | MemoryCache, options: LLMRequest, scope: 'touched' | 'all' = 'touched'): Promise<void> {
+		const store = this.access(memories);
+		const targets = scope === 'all' ? store.list : store.list.filter(m => m.content.includes(FACTS_HEADING));
+		await Promise.all(targets.map(node => this.reconcile(node, memories, options)));
+		store.commit();
 	}
 }
diff --git a/tests/llm.spec.ts b/tests/llm.spec.ts
deleted file mode 100644
index 2e887cd..0000000
--- a/tests/llm.spec.ts
+++ /dev/null
@@ -1,167 +0,0 @@
-
-import {describe, it, expect, vi, beforeEach} from 'vitest';
-import LLM from '../src/llm';
-
-const {FakeProvider, providerLog} = vi.hoisted(() => {
-	const providerLog: any[] = [];
-	class FakeProvider {
-		model: string;
-		constructor(...args: any[]) { this.model = args[args.length - 1]; }
-		ask(message: string, opts: any) {
-			let aborted = false;
-			const p = (async () => {
-				const script = (globalThis as any).__scripts?.[this.model];
-				const plan = script ? script(message, opts) : {text: ''};
-				providerLog.push({model: this.model, message, system: opts.system, tools: (opts.tools || []).map((t: any) => t.name)});
-				for (const c of plan.calls || []) {
-					if (aborted) break;
-					const tool = (opts.tools || []).find((t: any) => t.name === c.tool);
-					const id = c.id || `${c.tool}_${Math.random()}`;
-					const content = await tool.fn(c.args, opts.stream, null, id);
-					opts.history.push({role: 'tool', id, name: c.tool, args: c.args, content, timestamp: Date.now()});
-				}
-				const text = plan.text ?? '';
-				if (opts.stream && text) opts.stream({text, done: true});
-				opts.history.push({role: 'assistant', content: text, timestamp: Date.now(), duration: 10, tps: 5});
-				return text;
-			})();
-			return Object.assign(p, {abort: () => { aborted = true; }});
-		}
-	}
-	return {FakeProvider, providerLog};
-});
-
-vi.mock('../src/antrhopic.ts', () => ({Anthropic: FakeProvider}));
-vi.mock('../src/open-ai.ts', () => ({OpenAi: FakeProvider}));
-
-function makeAi(models: any) {
-	return {options: {llm: {models}}} as any;
-}
-
-beforeEach(() => {
-	providerLog.length = 0;
-	(globalThis as any).__scripts = {};
-});
-
-describe('LLM cross-provider interchangeability', () => {
-	it('runs identical tool calls the same way on an anthropic-backed model and an openai-backed model', async () => {
-		const ai = makeAi({
-			claude: {proto: 'anthropic', token: 'x'},
-			gpt: {proto: 'openai', token: 'y', host: 'http://local'},
-		});
-		const llm = new LLM(ai);
-		const calc = {
-			name: 'calc_add',
-			description: 'Add two numbers',
-			args: {a: {type: 'number', required: true}, b: {type: 'number', required: true}},
-			fn: (args: any) => String(args.a + args.b),
-		};
-
-		(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'calc_add', args: {a: 2, b: 3}}], text: 'Result: 5'});
-		(globalThis as any).__scripts.gpt = () => ({calls: [{tool: 'calc_add', args: {a: 2, b: 3}}], text: 'Result: 5'});
-
-		const historyA: any[] = [], historyB: any[] = [];
-		const respA = await llm.ask('add 2 and 3', {model: 'claude', tools: [calc], history: historyA});
-		const respB = await llm.ask('add 2 and 3', {model: 'gpt', tools: [calc], history: historyB});
-
-		expect(respA).toBe('Result: 5');
-		expect(respB).toBe('Result: 5');
-		expect(providerLog.find(l => l.model === 'claude')!.tools).toContain('calc_add');
-		expect(providerLog.find(l => l.model === 'gpt')!.tools).toContain('calc_add');
-
-		// tool timing gets recomputed from real execution regardless of proto
-		for (const h of [historyA.find(h => h.name === 'calc_add'), historyB.find(h => h.name === 'calc_add')]) {
-			expect(h.content).toBe('5');
-			expect(typeof h.duration).toBe('number');
-			expect(typeof h.tps).toBe('number');
-		}
-	});
-
-	it('lets the same shared history flow across model + proto swaps with different system prompts', async () => {
-		const ai = makeAi({
-			claude: {proto: 'anthropic', token: 'x'},
-			gpt: {proto: 'openai', token: 'y', host: 'http://local'},
-		});
-		const llm = new LLM(ai);
-		const history: any[] = [];
-
-		(globalThis as any).__scripts.claude = () => ({text: 'Hi from claude'});
-		(globalThis as any).__scripts.gpt = () => ({text: 'Hi from gpt'});
-
-		const r1 = await llm.ask('hello', {model: 'claude', system: 'You are terse.', history});
-		const r2 = await llm.ask('follow up', {model: 'gpt', system: 'You are verbose.', history});
-
-		expect(r1).toBe('Hi from claude');
-		expect(r2).toBe('Hi from gpt');
-		expect(history.filter(h => h.role === 'assistant').map(h => h.content)).toEqual(['Hi from claude', 'Hi from gpt']);
-		expect(providerLog[0].system).toContain('You are terse.');
-		expect(providerLog[1].system).toContain('You are verbose.');
-	});
-
-	it('exposes MCP tools the same way no matter which proto backs the model', async () => {
-		const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
-		const llm = new LLM(ai);
-		const mcp = [{name: 'weather', host: 'http://mcp.local'}];
-
-		global.fetch = vi.fn(async (url: string, opts?: any) => {
-			if (url.endsWith('/tools')) {
-				return {json: async () => ({tools: [{name: 'lookup', description: 'Look up weather', inputSchema: {properties: {city: {type: 'string'}}, required: ['city']}}]})} as any;
-			}
-			const body = JSON.parse(opts.body);
-			return {json: async () => ({content: [{text: `Sunny in ${body.arguments.city}`}]})} as any;
-		}) as any;
-
-		for (const model of ['claude', 'gpt']) {
-			(globalThis as any).__scripts[model] = () => ({calls: [{tool: 'weather_lookup', args: {city: 'Rome'}}], text: 'done'});
-			const history: any[] = [];
-			await llm.ask('weather?', {model, mcp, history});
-			expect(history.find(h => h.name === 'weather_lookup')?.content).toBe('Sunny in Rome');
-		}
-	});
-
-	it('exposes and resolves skill documents identically across protos', async () => {
-		const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
-		const llm = new LLM(ai);
-		const skills = [{name: 'Onboarding', description: 'How to onboard a user', content: 'Step 1...'}];
-
-		for (const model of ['claude', 'gpt']) {
-			(globalThis as any).__scripts[model] = () => ({calls: [{tool: 'skill_read', args: {name: 'Onboarding'}}], text: 'done'});
-			const history: any[] = [];
-			await llm.ask('onboard me', {model, skills, history});
-			expect(history.find(h => h.name === 'skill_read')?.content).toContain('Step 1...');
-		}
-	});
-
-	it('delegate agent mutates the shared history directly and backfills the orchestrator response, across protos', async () => {
-		const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
-		const llm = new LLM(ai);
-		const history: any[] = [{role: 'user', content: 'research quantum computing'}];
-		const researcher = {name: 'researcher', system: 'You research topics.', delegate: true, model: 'gpt'};
-
-		(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'agent_researcher', args: {}}], text: ''});
-		(globalThis as any).__scripts.gpt = () => ({text: 'Quantum computers use qubits.'});
-
-		const resp = await llm.ask('go', {model: 'claude', agents: [researcher], history});
-
-		expect(resp).toBe('Quantum computers use qubits.');
-		expect(history.some(h => h.role === 'assistant' && h.content === 'Quantum computers use qubits.')).toBe(true);
-		expect(history.find(h => h.name === 'agent_researcher')?.content).toBe('');
-	});
-
-	it('regular (non-delegate) subagent keeps its own isolated history separate from the parent, across protos', async () => {
-		const ai = makeAi({claude: {proto: 'anthropic', token: 'x'}, gpt: {proto: 'openai', token: 'y', host: 'http://local'}});
-		const llm = new LLM(ai);
-		const history: any[] = [];
-		const summarizer = {name: 'summarizer', system: 'You summarize text.', model: 'gpt'};
-
-		(globalThis as any).__scripts.claude = () => ({calls: [{tool: 'subagent_summarizer', args: {context: 'a long article', instructions: 'summarize it'}}], text: 'Summary: short version'});
-		(globalThis as any).__scripts.gpt = () => ({text: 'short version'});
-
-		const resp = await llm.ask('summarize this', {model: 'claude', agents: [summarizer], history});
-
-		expect(resp).toBe('Summary: short version');
-		expect(history.find(h => h.name === 'subagent_summarizer')?.content).toBe('short version');
-		// isolated history - subagent's own assistant turn never leaks into the parent
-		expect(history.some(h => h.role === 'assistant' && h.content === 'short version')).toBe(false);
-	});
-});
diff --git a/tests/memory.spec.ts b/tests/memory.spec.ts
deleted file mode 100644
index 6e2da0c..0000000
--- a/tests/memory.spec.ts
+++ /dev/null
@@ -1,256 +0,0 @@
-import {describe, it, expect, vi, beforeEach} from 'vitest';
-import {MemoryManager, MemoryCache, rebuildGraph, Memory} from '../src/memory';
-
-function makeMemory(overrides: Partial<Memory> = {}): Memory {
-	return {
-		name: 'Test/Doc',
-		description: '',
-		content: '',
-		embedding: [],
-		links: [],
-		backlinks: [],
-		...overrides,
-	};
-}
-
-function makeLLM() {
-	return {
-		embedding: vi.fn(async (_text: string) => [{embedding: [1, 0, 0]}]),
-		ask: vi.fn(async () => undefined),
-	};
-}
-
-describe('rebuildGraph', () => {
-	it('extracts [[WikiLinks]] from content, excluding self-links', () => {
-		const a = makeMemory({name: 'A', content: '[[B]] and [[A]] and [[C]]'});
-		const b = makeMemory({name: 'B', content: 'no links here'});
-		const mem = [a, b];
-
-		rebuildGraph(mem);
-
-		expect(a.links).toEqual(['B', 'C']);
-		expect(b.links).toEqual([]);
-	});
-
-	it('computes backlinks only for links that resolve to a real node', () => {
-		const a = makeMemory({name: 'A', content: '[[B]] [[Missing]]'});
-		const b = makeMemory({name: 'B', content: ''});
-		const mem = [a, b];
-
-		rebuildGraph(mem);
-
-		expect(b.backlinks).toEqual(['A']);
-		expect(mem.find(m => m.name === 'Missing')).toBeUndefined();
-	});
-
-	it('resets stale backlinks on every rebuild (no leftover from a removed link)', () => {
-		const a = makeMemory({name: 'A', content: '[[B]]'});
-		const b = makeMemory({name: 'B', content: ''});
-		const mem = [a, b];
-		rebuildGraph(mem);
-		expect(b.backlinks).toEqual(['A']);
-
-		a.content = 'no more links';
-		rebuildGraph(mem);
-		expect(b.backlinks).toEqual([]);
-	});
-});
-
-describe('MemoryCache', () => {
-	it('finds nearest neighbor by embedding via KD-tree search', () => {
-		const close = makeMemory({name: 'Close', embedding: [1, 0, 0]});
-		const far = makeMemory({name: 'Far', embedding: [0, 0, 1]});
-		const cache = new MemoryCache([close, far]);
-
-		const results = cache.search([1, 0, 0], 1);
-
-		expect(results[0].name).toBe('Close');
-	});
-
-	it('rebuilds the tree on add/update/remove', () => {
-		const cache = new MemoryCache([makeMemory({name: 'A', embedding: [1, 0, 0]})]);
-		cache.add(makeMemory({name: 'B', embedding: [0, 1, 0]}));
-		expect(cache.search([0, 1, 0], 1)[0].name).toBe('B');
-
-		cache.remove('B');
-		expect(cache.search([0, 1, 0], 1)[0]?.name).not.toBe('B');
-	});
-});
-
-describe('MemoryManager.forget', () => {
-	it('removes the node and recomputes backlinks for the rest of the graph', () => {
-		const llm = makeLLM();
-		const mgr = new MemoryManager(llm);
-		const a = makeMemory({name: 'A', content: '[[B]]'});
-		const b = makeMemory({name: 'B', content: '[[C]]'});
-		const c = makeMemory({name: 'C', content: ''});
-		const mem = [a, b, c];
-		rebuildGraph(mem);
-		expect(c.backlinks).toEqual(['B']);
-
-		const ok = mgr.forget('B', mem);
-
-		expect(ok).toBe(true);
-		expect(mem.find(m => m.name === 'B')).toBeUndefined();
-		expect(a.links).toEqual(['B']);
-		expect(c.backlinks).toEqual([]);
-	});
-
-	it('returns false for an unknown name', () => {
-		const mgr = new MemoryManager(makeLLM());
-		expect(mgr.forget('Nope', [makeMemory({name: 'A'})])).toBe(false);
-	});
-});
-
-describe('MemoryManager.recollect', () => {
-	it('orders vector matches first, then expands one hop via links', async () => {
-		const llm = makeLLM();
-		llm.embedding.mockResolvedValue([{embedding: [1, 0, 0]}]);
-		const mgr = new MemoryManager(llm);
-
-		const near = makeMemory({name: 'Near', embedding: [1, 0, 0], content: '[[Linked]]'});
-		const linked = makeMemory({name: 'Linked', embedding: [0, 0, 1], content: ''});
-		const far = makeMemory({name: 'Far', embedding: [0, 1, 0], content: ''});
-		const mem = [near, linked, far];
-		rebuildGraph(mem);
-
-		const result = await mgr.recollect('query', mem, 1, 1);
-
-		expect(result.map(r => r.name)).toEqual(['Near', 'Linked']);
-	});
-
-	it('returns [] when there are no memories', async () => {
-		const mgr = new MemoryManager(makeLLM());
-		expect(await mgr.recollect('q', [])).toEqual([]);
-	});
-});
-
-describe('MemoryManager.memorize (fast path)', () => {
-	let llm: ReturnType<typeof makeLLM>;
-	let mgr: MemoryManager;
-
-	beforeEach(() => {
-		llm = makeLLM();
-		mgr = new MemoryManager(llm);
-	});
-
-	it('pushes a pending tool message, then resolves it to links once facts land', async () => {
-		llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
-			if (opts.tools) {
-				opts.tools[0].fn({destination: 'Projects/Oxide', facts: 'Uses a hybrid memory system'});
-				return undefined;
-			}
-			return {description: 'd', content: '# doc'};
-		});
-
-		const history: any[] = [{role: 'user', content: 'we use a hybrid memory system'}];
-		const touched = await mgr.memorize(history, [], {model: 'test'} as any);
-
-		const pending = history.find(h => h.name === 'memory_process');
-		expect(pending).toBeDefined();
-		expect(pending.content).toContain('[[Projects/Oxide]]');
-		expect(touched.map(t => t.name)).toEqual(['Projects/Oxide']);
-	});
-
-	it('creates a new node and appends facts under "## Facts" without calling the doc LLM', async () => {
-		llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
-			if (opts.tools) opts.tools[0].fn({destination: 'People/Sarah', facts: 'Works at Acme, Likes hiking'});
-			return undefined;
-		});
-
-		const mem: Memory[] = [];
-		await mgr.memorize([{role: 'user', content: 'Sarah works at Acme and likes hiking'}] as any, mem, {model: 'test'} as any);
-
-		const node = mem.find(m => m.name === 'People/Sarah')!;
-		expect(node).toBeDefined();
-		expect(node.content).toContain('## Facts');
-		expect(node.content).toContain('- Works at Acme');
-		expect(node.content).toContain('- Likes hiking');
-		// doc reconciler LLM (schema call) should NOT have been awaited synchronously in this fast path assertion
-	});
-
-	it('routes "journal" destination to Journal/{weekMonday}', async () => {
-		llm.ask.mockImplementation(async (_prompt: string, opts: any) => {
-			if (opts.tools) opts.tools[0].fn({destination: 'journal', facts: 'Shipped v1'});
-			return undefined;
-		});
-
-		const mem: Memory[] = [];
-		const touched = await mgr.memorize([{role: 'user', content: 'shipped v1 today'}] as any, mem, {model: 'test'} as any);
-
-		expect(touched[0].name).toMatch(/^Journal\/\d{4}-\d{2}-\d{2}$/);
-	});
-
-	it('reports nothing to remember when no facts are extracted', async () => {
-		llm.ask.mockResolvedValue(undefined); // tools present but fn never called
-
-		const history: any[] = [{role: 'user', content: 'hey'}];
-		const touched = await mgr.memorize(history, [], {model: 'test'} as any);
-
-		expect(touched).toEqual([]);
-		expect(history.find(h => h.name === 'memory_process').content).toBe('Nothing worth remembering.');
-	});
-
-	it('returns [] and does nothing for an empty conversation', async () => {
-		const touched = await mgr.memorize([], [], {model: 'test'} as any);
-		expect(touched).toEqual([]);
-		expect(llm.ask).not.toHaveBeenCalled();
-	});
-});
-
-describe('MemoryManager reconcileVault', () => {
-	it('integrates the "## Facts" section via the doc LLM and removes it', async () => {
-		const llm = makeLLM();
-		llm.ask.mockResolvedValue({description: 'Tidy summary', content: '# Doc\n\nIntegrated fact.'});
-		const mgr = new MemoryManager(llm);
-
-		const node = makeMemory({
-			name: 'Projects/Oxide',
-			content: '---\nname: Projects/Oxide\n---\n\n# Doc\n\n## Facts\n- some raw fact\n',
-		});
-		const mem = [node];
-
-		await mgr.reconcileVault(mem, {model: 'test'} as any, 'all');
-
-		expect(node.content).not.toContain('## Facts');
-		expect(node.content).toContain('Integrated fact.');
-		expect(node.description).toBe('Tidy summary');
-	});
-
-	it('only targets docs with a pending Facts inbox when scope is "touched"', async () => {
-		const llm = makeLLM();
-		llm.ask.mockResolvedValue({description: 'd', content: '# clean'});
-		const mgr = new MemoryManager(llm);
-
-		const dirty = makeMemory({name: 'A', content: '## Facts\n- x'});
-		const clean = makeMemory({name: 'B', content: '# already tidy'});
-		await mgr.reconcileVault([dirty, clean], {model: 'test'} as any, 'touched');
-
-		expect(dirty.content).toContain('# clean'); // rewritten (frontmatter now wraps it)
-		expect(clean.content).toBe('# already tidy'); // untouched, never queued
-	});
-});
-
-describe('MemoryManager reconcile coalescing', () => {
-	it('coalesces a second call while one is in-flight: marks dirty, aborts, reuses the same task promise', () => {
-		const llm = makeLLM();
-		const abort = vi.fn();
-		let calls = 0;
-		llm.ask.mockImplementation(() => {
-			calls++;
-			const pending: any = new Promise(() => {}); // never resolves in this test
-			pending.abort = abort;
-			return pending;
-		});
-		const mgr: any = new MemoryManager(llm);
-		const node = makeMemory({name: 'Q', content: '# Q\n\n## Facts\n- f'});
-		const mem = [node];
-
-		const p1 = mgr.reconcile(node, mem, {model: 'test'});
-		const p2 = mgr.reconcile(node, mem, {model: 'test'});
-
-		expect(p2).toBe(p1); // same in-flight task, not a new queue entry
-		expect(abort).toHaveBeenCalledTimes(1); // second call aborted the in-flight request
-		expect(calls).toBe(1); // no second ask() fired synchronously — it'll rerun via the dirty loop
-	});
-});