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Use this skill when implementing memory for AI agents. Activate when the user needs agents to remember past interactions, implement context persistence, build knowledge bases for agents, design agent state management, or create shared memory between multiple agents.
This skill uses the workspace's default tool permissions.
Agent Memory Systems
Design and implement memory systems that give agents persistent knowledge and context.
When to Use
- Agents need to remember across sessions
- Multiple agents share knowledge
- Long-running tasks require state persistence
- Building agents that learn from experience
Memory Types
┌─────────────────────────────────────────────────────────────┐
│ AGENT MEMORY TAXONOMY │
├─────────────────────────────────────────────────────────────┤
│ │
│ Working Memory (Active Context) │
│ └─ Current conversation, immediate task state │
│ │
│ Short-Term Memory (Session) │
│ └─ Recent interactions, temporary facts │
│ │
│ Long-Term Memory (Persistent) │
│ ├─ Episodic: Past events, experiences │
│ ├─ Semantic: Facts, knowledge, learned info │
│ └─ Procedural: How to do things, skills │
│ │
└─────────────────────────────────────────────────────────────┘
Working Memory
The agent's current context window.
interface WorkingMemory {
// Current task context
task: {
description: string;
requirements: string[];
progress: string[];
};
// Active entities being discussed
entities: Map<string, Entity>;
// Recent messages
conversationWindow: Message[];
// Scratchpad for reasoning
scratchpad: string;
}
class WorkingMemoryManager {
private memory: WorkingMemory;
private MAX_MESSAGES = 20;
addMessage(message: Message) {
this.memory.conversationWindow.push(message);
// Evict old messages
if (this.memory.conversationWindow.length > this.MAX_MESSAGES) {
const evicted = this.memory.conversationWindow.shift();
// Optionally summarize and store
this.summarizeToShortTerm(evicted);
}
}
updateEntity(id: string, entity: Entity) {
this.memory.entities.set(id, entity);
}
getContext(): string {
return `
Task: ${this.memory.task.description}
Progress: ${this.memory.task.progress.join(', ')}
Key Entities: ${[...this.memory.entities.values()].map(e => e.summary).join('\n')}
Recent Discussion: ${this.memory.conversationWindow.slice(-5).map(m => m.content).join('\n')}
`;
}
}
Short-Term Memory
Session-scoped, expires after inactivity.
interface ShortTermMemory {
sessionId: string;
startedAt: Date;
lastAccessedAt: Date;
expiresAt: Date;
// Conversation summary
summary: string;
// Key facts learned this session
facts: Fact[];
// Decisions made
decisions: Decision[];
// Files accessed
touchedFiles: string[];
}
class ShortTermStore {
private store = new Map<string, ShortTermMemory>();
private TTL_MS = 30 * 60 * 1000; // 30 minutes
async get(sessionId: string): Promise<ShortTermMemory | null> {
const memory = this.store.get(sessionId);
if (!memory) return null;
if (Date.now() > memory.expiresAt.getTime()) {
// Expired - archive to long-term
await this.archiveToLongTerm(memory);
this.store.delete(sessionId);
return null;
}
// Touch
memory.lastAccessedAt = new Date();
memory.expiresAt = new Date(Date.now() + this.TTL_MS);
return memory;
}
async addFact(sessionId: string, fact: Fact) {
const memory = await this.getOrCreate(sessionId);
memory.facts.push(fact);
// Check if fact should be promoted to long-term
if (this.shouldPromote(fact)) {
await this.promoteToLongTerm(fact);
}
}
}
Long-Term Memory
Episodic Memory (Events/Experiences)
interface Episode {
id: string;
timestamp: Date;
type: 'task_completed' | 'error_resolved' | 'user_feedback' | 'learning';
// What happened
description: string;
context: Record<string, unknown>;
// Outcome
outcome: 'success' | 'failure' | 'partial';
lessons: string[];
// For retrieval
embedding: number[];
tags: string[];
}
class EpisodicMemory {
private vectorStore: VectorStore;
async remember(episode: Episode): Promise<void> {
// Generate embedding for semantic search
episode.embedding = await this.embed(
`${episode.description} ${episode.lessons.join(' ')}`
);
await this.vectorStore.insert(episode);
}
async recall(query: string, limit: number = 5): Promise<Episode[]> {
const queryEmbedding = await this.embed(query);
return this.vectorStore.similaritySearch(queryEmbedding, {
limit,
threshold: 0.7
});
}
async recallByType(type: Episode['type'], limit: number = 10): Promise<Episode[]> {
return this.vectorStore.filter({ type }, { limit, orderBy: 'timestamp DESC' });
}
}
Semantic Memory (Facts/Knowledge)
interface Fact {
id: string;
subject: string;
predicate: string;
object: string;
confidence: number;
source: string;
learnedAt: Date;
lastVerified: Date;
embedding: number[];
}
class SemanticMemory {
private facts: VectorStore<Fact>;
async learn(fact: Omit<Fact, 'id' | 'embedding'>): Promise<void> {
// Check for conflicts
const existing = await this.findRelated(fact.subject, fact.predicate);
if (existing.length > 0) {
// Handle contradiction or update
await this.resolveConflict(existing, fact);
return;
}
// Store new fact
await this.facts.insert({
...fact,
id: generateId(),
embedding: await this.embed(`${fact.subject} ${fact.predicate} ${fact.object}`)
});
}
async query(question: string): Promise<Fact[]> {
// Semantic search for relevant facts
const embedding = await this.embed(question);
return this.facts.similaritySearch(embedding, { limit: 10 });
}
async getFactsAbout(subject: string): Promise<Fact[]> {
return this.facts.filter({ subject });
}
}
Procedural Memory (Skills/How-To)
interface Procedure {
id: string;
name: string;
description: string;
trigger: string; // When to use this
steps: string[];
examples: Example[];
successRate: number;
usageCount: number;
}
class ProceduralMemory {
private procedures: Map<string, Procedure> = new Map();
async findProcedure(task: string): Promise<Procedure | null> {
// Match task to known procedures
const candidates = await this.matchProcedures(task);
if (candidates.length === 0) return null;
// Return best match by success rate and relevance
return candidates.sort((a, b) =>
(b.successRate * b.relevanceScore) - (a.successRate * a.relevanceScore)
)[0];
}
async recordOutcome(procedureId: string, success: boolean): Promise<void> {
const proc = this.procedures.get(procedureId);
if (!proc) return;
// Update success rate with exponential moving average
const alpha = 0.1;
proc.successRate = alpha * (success ? 1 : 0) + (1 - alpha) * proc.successRate;
proc.usageCount++;
}
async learnProcedure(
name: string,
steps: string[],
fromEpisode: Episode
): Promise<void> {
// Create new procedure from successful episode
this.procedures.set(generateId(), {
id: generateId(),
name,
description: fromEpisode.description,
trigger: this.extractTrigger(fromEpisode),
steps,
examples: [{ input: fromEpisode.context, output: fromEpisode.outcome }],
successRate: 1.0,
usageCount: 1
});
}
}
Shared Memory (Multi-Agent)
interface SharedMemory {
// Namespace for isolation
namespace: string;
// Read/write with locking
read(key: string): Promise<unknown>;
write(key: string, value: unknown): Promise<void>;
// Atomic operations
compareAndSwap(key: string, expected: unknown, newValue: unknown): Promise<boolean>;
// Subscriptions
subscribe(pattern: string, callback: (key: string, value: unknown) => void): void;
}
class RedisSharedMemory implements SharedMemory {
constructor(
private redis: Redis,
public namespace: string
) {}
private key(k: string): string {
return `${this.namespace}:${k}`;
}
async read(key: string): Promise<unknown> {
const value = await this.redis.get(this.key(key));
return value ? JSON.parse(value) : null;
}
async write(key: string, value: unknown): Promise<void> {
await this.redis.set(this.key(key), JSON.stringify(value));
await this.redis.publish(`${this.namespace}:updates`, JSON.stringify({ key, value }));
}
subscribe(pattern: string, callback: (key: string, value: unknown) => void): void {
const subscriber = this.redis.duplicate();
subscriber.psubscribe(`${this.namespace}:${pattern}`);
subscriber.on('pmessage', (_, channel, message) => {
const { key, value } = JSON.parse(message);
callback(key, value);
});
}
}
Memory Retrieval Strategies
Strategy 1: Recency-Weighted
function recencyWeightedRetrieval(
memories: Memory[],
query: string,
recencyWeight: number = 0.3
): Memory[] {
const now = Date.now();
return memories
.map(m => ({
memory: m,
score: (1 - recencyWeight) * m.relevanceScore +
recencyWeight * Math.exp(-(now - m.timestamp.getTime()) / TIME_DECAY)
}))
.sort((a, b) => b.score - a.score)
.map(x => x.memory);
}
Strategy 2: Importance-Based
function importanceBasedRetrieval(
memories: Memory[],
query: string
): Memory[] {
return memories
.map(m => ({
memory: m,
score: m.relevanceScore * m.importance * (m.accessCount / 10)
}))
.sort((a, b) => b.score - a.score)
.map(x => x.memory);
}
Strategy 3: Contextual (RAG)
async function contextualRetrieval(
query: string,
currentContext: Context
): Promise<Memory[]> {
// Expand query with context
const expandedQuery = `
${query}
Current task: ${currentContext.task}
Related entities: ${currentContext.entities.join(', ')}
`;
// Vector search
const candidates = await vectorStore.search(expandedQuery, { limit: 20 });
// Rerank with cross-encoder
return reranker.rerank(query, candidates, { limit: 5 });
}
Memory Maintenance
class MemoryMaintenance {
// Consolidate short-term to long-term
async consolidate(): Promise<void> {
const sessions = await shortTermStore.getExpired();
for (const session of sessions) {
// Extract key learnings
const learnings = await this.extractLearnings(session);
// Store in appropriate long-term stores
for (const learning of learnings) {
if (learning.type === 'fact') {
await semanticMemory.learn(learning);
} else if (learning.type === 'procedure') {
await proceduralMemory.learnProcedure(learning);
} else {
await episodicMemory.remember(learning);
}
}
}
}
// Forget outdated/irrelevant memories
async forget(): Promise<void> {
// Remove low-value memories
await episodicMemory.prune({
olderThan: days(90),
accessCountBelow: 2,
importanceBelow: 0.2
});
// Update fact confidence based on verification
await semanticMemory.decayUnverified({
olderThan: days(30),
decayRate: 0.1
});
}
}
Best Practices
- Separate concerns - Different memory types for different purposes
- Index wisely - Use embeddings for semantic search
- Expire aggressively - Don't let memory grow unbounded
- Version memories - Track when facts were learned/updated
- Handle conflicts - New information may contradict old
- Secure sensitive data - Some memories shouldn't be shared
Similar Skills
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.