Rebuild graph edges on changes

package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@ztimson/ai-utils",
-	"version": "1.4.2",
+	"version": "1.4.4",
 	"description": "AI Utility library",
 	"author": "Zak Timson",
 	"license": "MIT",

src/llm.ts

@@ -132,8 +132,8 @@ class LLM {
 			return {
 				name: toolName,
 				description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
-				args: <any>(a.delegate ? {} : {
-					context: {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true},
+				args: <any>({
+					context: !a.delegate ? {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true} : undefined,
 					instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
 				}),
 				fn: async (args: any, stream: any, ai: any, id?: string) => {
@@ -148,8 +148,9 @@ class LLM {
 					const q = a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`;
 
 					const request = this.ask(q, {
-						system: `You are a specialized subagent. ${a.delegate ? 'Your output streams directly to the user for the remainder of this turn. You are mid conversation - dispense with greetings.' : 'You are wrapped in a tool call that will be analysis by an LLM - dispense with conversation'}
-As a subagent, focus on executing your task completely using available tools and returning only the final result - no commentary, questions, or dialogue.
+						system: `You are a specialized subagent being called from an orchestrator
+${a.delegate ? 'Your output streams directly to the user for the remainder of this turn. You are mid conversation' : 'You are wrapped in a tool call that will be analysis by an LLM'}
+Dispense with greetings and focus on your instructions using available tools and returning only the final result unless specifically instructed to converse
 
 ${a.system}`,
 						model: a.model || undefined,
@@ -272,8 +273,6 @@ ${a.system}`,
 		promise = (async () => {
 			let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
 			const prompts: string[] = [];
-			// `history` is the single source of truth from here on - mutated in place by
-			// this call AND by any nested/delegated agent calls sharing the same array
 			let history = options.history || [];
 			if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
 
@@ -329,7 +328,8 @@ ${r.description}
 ${r.content}
 `).join('\n---\n')}
 ` : ''}${listed.length ? `
-Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.name).join(', ')}
+Additional relevant memories (use \`memory_recall\`):
+${listed.map(r => r.name).join(', ')}
 ` : ''}`.trim());
 					}
 					if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
@@ -344,8 +344,6 @@ Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.nam
 			if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
 
 			prompts.unshift(options.system || this.ai.options.llm?.system || '');
-			// Message already appended to shared `history` above - pass '' so the provider
-			// doesn't push a duplicate user turn
 			request = this.models[m].ask('', {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
 			let resp = await request;
 

src/memory.ts

@@ -43,6 +43,7 @@ export class MemoryCache {
 
 	add(memory: Memory): void {
 		this.memories.push(memory);
+		rebuildGraph(this.memories);
 		this.rebuild();
 	}
 
@@ -53,6 +54,7 @@ export class MemoryCache {
 		} else {
 			this.memories.push(memory);
 		}
+		rebuildGraph(this.memories);
 		this.rebuild();
 	}
 
@@ -60,6 +62,7 @@ export class MemoryCache {
 		const idx = this.memories.findIndex(m => m.name === name);
 		if (idx !== -1) {
 			this.memories.splice(idx, 1);
+			rebuildGraph(this.memories);
 			this.rebuild();
 		}
 	}
@@ -186,6 +189,17 @@ export class MemoryManager {
 
 	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;
 		const raw = m instanceof MemoryCache || Array.isArray(m);
@@ -458,6 +472,8 @@ ${currentBody}
 
 	private async factAgent(conversation: string, memories: Memory[], options: LLMRequest, weekKey: string): Promise<FactBucket[]> {
 		const buckets = new Map<string, string[]>();
+		const ghosts = this.ghostNodes(memories);
+
 		await this.llm.ask(conversation, {
 			model: options.model,
 			temperature: 0.2,
@@ -472,14 +488,15 @@ Rules:
 - If nothing worth remembering was said, do not call any tools
 
 When extracting facts, you MUST also decide the exact destination path:
-- Use an existing node name if the facts clearly belong there
+- 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"
 
 Available nodes:
 - Journal
-${this.listNodes(memories).filter(n => !n.name.includes('Journal')).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}`,
+${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',