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+# API Reference
+
+This reference describes the public exports visible from `src/index.ts`:
+
+```ts
+export * from './types';
+export * from './memory';
+export * from './schedule';
+export * from './conversation';
+export * from './persona';
+```
+
+## `Persona`
+
+Main framework class.
+
+### Constructors
+
+```ts
+new Persona(displayName: string, seedMessage: string, options?: PersonaOptions)
+new Persona(spaceId: string, options?: PersonaOptions)
+```
+
+Create mode:
+
+```ts
+const persona = new Persona('Mina', 'Mina likes quiet cafes.', { memory, models });
+```
+
+Load mode:
+
+```ts
+const persona = new Persona(existingSpaceId, { memory, models });
+```
+
+Behavior:
+
+- Create mode calls `memory.createSpace({ displayName, seedMessage, now })`.
+- Load mode calls `memory.getSpace(spaceId)` and throws if missing.
+- Initialization starts immediately in the constructor and is awaited through `ready()`.
+- If `options.memory` is omitted, an `InMemoryMemoryStore` is used.
+
+### `ready()`
+
+```ts
+ready(): Promise<MemorySpace>
+```
+
+Returns the created or loaded persona memory space.
+
+### `createDailySchedule(datetime, message)`
+
+```ts
+createDailySchedule(datetime: DateTimeInput, message: string): Promise<ScheduleEntry[]>
+```
+
+Creates tomorrow's 10-minute schedule.
+
+If `datetime` is May 1, the schedule covers May 2 00:00 through May 3 00:00 and contains 144 entries.
+
+Side effects:
+
+- saves entries through `memory.saveScheduleEntries`
+- refreshes the in-memory availability snapshot
+- emits `persona.schedule.daily.generated`
+
+Current deterministic mapping:
+
+- message containing travel/trip/여행 -> daytime `travel`
+- message containing study/exam/공부/시험 -> daytime `study`
+- message containing job/취업/구직 -> daytime `job-search`
+- message containing work/일/회사 -> daytime `work`
+- otherwise daytime defaults to `work`
+
+### `createMonthlySchedule(datetime, message)`
+
+```ts
+createMonthlySchedule(datetime: DateTimeInput, message: string): Promise<ScheduleEntry[]>
+```
+
+Creates 30 day-level entries starting tomorrow.
+
+Side effects:
+
+- saves entries through `memory.saveScheduleEntries`
+- refreshes availability
+- emits `persona.schedule.monthly.generated`
+
+### `deleteSchedulesBefore(cutoffExclusive)`
+
+```ts
+deleteSchedulesBefore(cutoffExclusive: DateTimeInput): Promise<number>
+```
+
+Deletes or marks schedule entries before a caller-provided cutoff.
+
+Behavior depends on the memory store:
+
+- `InMemoryMemoryStore` physically removes entries whose `endAt <= cutoffExclusive` and returns the deleted count.
+- `IdentityDbMemoryStore` currently cannot physically delete schedule facts through IdentityDB's public append-oriented API, so it returns `0` at the store layer.
+- The `Persona` layer always records a fact with topic `persona.schedule.deleted` and source `boxbrain.schedule.prune`.
+
+### `deleteSchedulesOlderThan(datetime)`
+
+```ts
+deleteSchedulesOlderThan(datetime: DateTimeInput): Promise<number>
+```
+
+Alias for `deleteSchedulesBefore(datetime)`.
+
+### `getTodayScheduledAvailability(datetime)`
+
+```ts
+getTodayScheduledAvailability(datetime: DateTimeInput): Promise<ScheduledAvailabilitySnapshot>
+```
+
+Returns the cached schedule-derived availability snapshot.
+
+Window rule:
+
+- start: UTC start of `datetime`'s day
+- end: two UTC days later
+
+If the snapshot is missing or the day changed, BoxBrain reloads schedule entries from memory and rebuilds the snapshot.
+
+### `sendMessage(input)`
+
+```ts
+sendMessage(input: {
+  datetime: DateTimeInput;
+  messageHistory: PersonaMessage[];
+  getLatestMessageHistory?: () => Promise<PersonaMessage[]>;
+}): Promise<OutgoingMessageDraft>
+```
+
+Generates a reply to the user's message history.
+
+Requires:
+
+```ts
+options.models.conversation
+```
+
+Pipeline:
+
+1. Await persona readiness.
+2. Load current availability.
+3. Build mandatory conversation context:
+   - formatted `messageHistory`
+   - schedule entries from yesterday through tomorrow
+   - availability snapshot
+   - facts tagged with `persona`, the persona display name, or `user`
+4. Emit `persona.conversation.context.loaded`.
+5. Call `models.conversation.generateReply` with mode `reply`.
+6. Trim blank messages from the draft.
+7. If `getLatestMessageHistory` and `models.rewrite` are present, check whether a newer history arrived and optionally rewrite.
+8. Emit `persona.conversation.reply.generated`.
+9. Return `OutgoingMessageDraft`.
+
+Throws if no conversation model is configured.
+
+### `startConversation(input)`
+
+```ts
+startConversation(input: {
+  datetime: DateTimeInput;
+  messageHistory: PersonaMessage[];
+}): Promise<OutgoingMessageDraft>
+```
+
+Generates a proactive opener from the persona.
+
+Requires:
+
+```ts
+options.models.conversation
+```
+
+Uses the same mandatory context pipeline as `sendMessage`, but passes `mode: 'start-conversation'` to the model.
+
+Emits `persona.conversation.started`.
+
+### `sleepMemory(input)`
+
+```ts
+sleepMemory(input: {
+  datetime: DateTimeInput;
+  messageHistory: PersonaMessage[];
+}): Promise<FactDraft[]>
+```
+
+Extracts durable facts from a period of messages and persists them.
+
+Requires:
+
+```ts
+options.models.memoryExtraction
+```
+
+Pipeline:
+
+1. Find current context facts tagged with `persona`, the persona display name, or `user`.
+2. Format the provided message history.
+3. Call `models.memoryExtraction.extract` with the objectivization instruction.
+4. Persist each returned fact through `memory.addFact`.
+5. Add the topic `sleepMemory` to each persisted fact.
+6. Use source `boxbrain.sleepMemory` if the draft did not specify a source.
+7. Emit `persona.memory.sleep.persisted`.
+8. Return the extracted drafts.
+
+Recommended cadence: daily around midnight, passing the previous day's messages.
+
+## Options and models
+
+### `PersonaOptions`
+
+```ts
+interface PersonaOptions {
+  memory?: BoxBrainMemoryStore;
+  models?: PersonaModels;
+  debug?: DebugHook;
+  now?: DateTimeInput;
+}
+```
+
+- `memory`: storage adapter. Defaults to `InMemoryMemoryStore`.
+- `models`: provider-agnostic LLM adapters.
+- `debug`: optional async event hook.
+- `now`: deterministic initialization time for tests or replay.
+
+### `PersonaModels`
+
+```ts
+interface PersonaModels {
+  initialization?: PersonaInitializationModel;
+  conversation?: ConversationModel;
+  rewrite?: RewriteModel;
+  memoryExtraction?: MemoryExtractionModel;
+}
+```
+
+### `PersonaInitializationModel`
+
+```ts
+interface PersonaInitializationModel {
+  extractInitialFacts(input: {
+    displayName: string;
+    seedMessage: string;
+    now: string;
+  }): Promise<FactDraft[]>;
+}
+```
+
+Called during persona creation. If omitted, BoxBrain stores a default seed fact. If it returns `[]`, BoxBrain stores no fallback fact.
+
+### `ConversationModel`
+
+```ts
+interface ConversationModel {
+  generateReply(input: ReplyGenerationInput): Promise<OutgoingMessageDraft>;
+}
+```
+
+### `ReplyGenerationInput`
+
+```ts
+interface ReplyGenerationInput {
+  persona: MemorySpace;
+  now: string;
+  mode: 'reply' | 'start-conversation';
+  context: MandatoryConversationContext;
+  userMessage?: string;
+  instruction: string;
+}
+```
+
+### `OutgoingMessageDraft`
+
+```ts
+interface OutgoingMessageDraft {
+  messages: string[];
+  reasoning?: string;
+}
+```
+
+The host app should deliver each `messages[]` item as a separate messenger message.
+
+### `RewriteModel`
+
+```ts
+interface RewriteModel {
+  decide(input: RewriteDecisionInput): Promise<RewriteDecision>;
+}
+```
+
+```ts
+interface RewriteDecision {
+  rewrite: boolean;
+  draft?: OutgoingMessageDraft;
+  reason?: string;
+}
+```
+
+### `MemoryExtractionModel`
+
+```ts
+interface MemoryExtractionModel {
+  extract(input: MemoryExtractionInput): Promise<FactDraft[]>;
+}
+```
+
+```ts
+interface MemoryExtractionInput {
+  persona: MemorySpace;
+  now: string;
+  formattedMessageHistory: string;
+  contextFacts: StoredFact[];
+  instruction: string;
+}
+```
+
+## Memory stores
+
+### `BoxBrainMemoryStore`
+
+```ts
+interface BoxBrainMemoryStore {
+  createSpace(input: { displayName: string; seedMessage: string; now: string }): Promise<MemorySpace>;
+  getSpace(spaceId: string): Promise<MemorySpace | null>;
+  addFact(spaceId: string, fact: FactDraft): Promise<StoredFact>;
+  listFacts(spaceId: string): Promise<StoredFact[]>;
+  findFacts(spaceId: string, topics: string[]): Promise<StoredFact[]>;
+  saveScheduleEntries(spaceId: string, entries: ScheduleEntry[]): Promise<void>;
+  listScheduleEntries(spaceId: string, fromInclusive: string, toExclusive: string): Promise<ScheduleEntry[]>;
+  deleteScheduleEntriesBefore(spaceId: string, cutoffExclusive: string): Promise<number>;
+}
+```
+
+### `InMemoryMemoryStore`
+
+Test/demo store backed by maps:
+
+- `spaces: Map<string, MemorySpace>`
+- `facts: Map<string, StoredFact[]>`
+- `schedules: Map<string, ScheduleEntry[]>`
+
+Useful for unit tests and demos. Not persistent.
+
+### `IdentityDbMemoryStore`
+
+Persistent store backed by IdentityDB.
+
+```ts
+import { IdentityDB } from 'identitydb';
+import { IdentityDbMemoryStore } from 'boxbrain';
+
+const db = await IdentityDB.connect({ client: 'sqlite', filename: '.data/personas.sqlite' });
+await db.initialize();
+const memory = new IdentityDbMemoryStore({ db });
+```
+
+### `createSqliteIdentityMemoryStore(filename)`
+
+```ts
+createSqliteIdentityMemoryStore(filename: string): Promise<IdentityDbMemoryStore>
+```
+
+Convenience helper that connects and initializes an IdentityDB SQLite database.
+
+## Core types
+
+### `DateTimeInput`
+
+```ts
+type DateTimeInput = Date | string | number;
+```
+
+All datetime inputs are converted through `new Date(...)`. Invalid dates throw.
+
+### `MemorySpace`
+
+```ts
+interface MemorySpace {
+  id: string;
+  displayName: string;
+  createdAt: string;
+  metadata: Record<string, unknown>;
+}
+```
+
+### `FactDraft`
+
+```ts
+interface FactDraft {
+  statement: string;
+  topics: string[];
+  confidence?: number;
+  source?: string;
+  metadata?: Record<string, unknown>;
+}
+```
+
+### `StoredFact`
+
+```ts
+interface StoredFact extends FactDraft {
+  id: string;
+  createdAt: string;
+}
+```
+
+### `PersonaMessage`
+
+```ts
+interface PersonaMessage {
+  sender: 'persona' | 'user';
+  time: DateTimeInput;
+  content: string;
+}
+```
+
+### `ScheduleActivity`
+
+```ts
+type ScheduleActivity =
+  | 'sleep'
+  | 'rest'
+  | 'meal'
+  | 'commute'
+  | 'work'
+  | 'study'
+  | 'job-search'
+  | 'travel'
+  | 'exercise'
+  | 'social'
+  | 'errand'
+  | 'free-time';
+```
+
+### `ScheduleEntry`
+
+```ts
+interface ScheduleEntry {
+  id: string;
+  spaceId: string;
+  startAt: string;
+  endAt: string;
+  activity: ScheduleActivity;
+  title: string;
+  description?: string;
+  granularity: 'day' | 'ten-minute';
+  sourceMessage?: string;
+  metadata: Record<string, unknown>;
+}
+```
+
+### `AvailabilityMode`
+
+```ts
+type AvailabilityMode = 'online' | 'do-not-disturb' | 'offline';
+```
+
+### `AvailabilityRange`
+
+```ts
+interface AvailabilityRange {
+  startAt: string;
+  endAt: string;
+  mode: AvailabilityMode;
+  sourceScheduleIds: string[];
+  reason: string;
+}
+```
+
+### `ScheduledAvailabilitySnapshot`
+
+```ts
+interface ScheduledAvailabilitySnapshot {
+  generatedAt: string;
+  windowStartAt: string;
+  windowEndAt: string;
+  ranges: AvailabilityRange[];
+}
+```
+
+### `MandatoryConversationContext`
+
+```ts
+interface MandatoryConversationContext {
+  formattedMessageHistory: string;
+  conversationWindowLabel: string;
+  memorySummary: string;
+  personaAndUserFacts: StoredFact[];
+  scheduleEntries: ScheduleEntry[];
+  availability: ScheduledAvailabilitySnapshot;
+}
+```
+
+## Schedule helper exports
+
+The following helpers are exported for applications and tests:
+
+```ts
+toDate(input)
+toIso(input)
+startOfUtcDay(input)
+addUtcDays(input, days)
+scheduleTargetDay(now)
+createTenMinuteDailySchedule(input)
+createMonthlyScheduleEntries(input)
+availabilityModeForEntry(entry)
+buildAvailabilitySnapshot(input)
+dateKeysAround(input)
+```
+
+## Conversation helper exports
+
+```ts
+formatMessageHistory({ personaName, messages })
+conversationInstruction()
+memoryExtractionInstruction(now)
+buildMandatoryConversationContext(input)
+```
+
+`formatMessageHistory` converts structured messages into model-readable text:
+
+```text
+Mina@2026-04-30T23:00:00.000Z: See you later.
+user@2026-05-01T12:00:00.000Z: What are you doing?
+```
diff --git a/Getting-Started.md b/Getting-Started.md
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+# Getting Started
+
+This page shows the shortest path from installation to a working BoxBrain persona.
+
+## Requirements
+
+- Bun `>= 1.2.0`
+- TypeScript
+- A model adapter object that implements BoxBrain's provider-agnostic interfaces
+- Optional but recommended: a SQLite-backed IdentityDB store via `createSqliteIdentityMemoryStore`
+
+## Install
+
+For local development inside the repository:
+
+```bash
+bun install
+bun run test
+bun run check
+bun run build
+```
+
+For a consuming app, install the package normally if it is available in your registry:
+
+```bash
+bun add boxbrain
+```
+
+If consuming directly from the Gitea repository, pin a commit for reproducibility:
+
+```bash
+bun add git+https://git.psw.kr/p-sw/BoxBrain.git#49f75af
+```
+
+## 1. Create a memory store
+
+Use `InMemoryMemoryStore` for tests and demos:
+
+```ts
+import { InMemoryMemoryStore } from 'boxbrain';
+
+const memory = new InMemoryMemoryStore();
+```
+
+Use SQLite + IdentityDB for persistent persona memory:
+
+```ts
+import { createSqliteIdentityMemoryStore } from 'boxbrain';
+
+const memory = await createSqliteIdentityMemoryStore('.data/personas.sqlite');
+```
+
+## 2. Provide model adapters
+
+BoxBrain does not hard-code OpenAI, xAI, OpenRouter, Anthropic, or any other provider. The host app supplies objects that match the model interfaces.
+
+A minimal conversation model:
+
+```ts
+import type { ConversationModel } from 'boxbrain';
+
+const conversation: ConversationModel = {
+  async generateReply(input) {
+    // Call your LLM here.
+    // input.instruction contains BoxBrain's chat-like send_message guidance.
+    // input.context contains message history, memory, schedule, and availability.
+    return {
+      messages: ['I was just studying a bit.', 'How about you?'],
+      reasoning: 'Short casual reply matching the persona.',
+    };
+  },
+};
+```
+
+A minimal memory extraction model:
+
+```ts
+import type { MemoryExtractionModel } from 'boxbrain';
+
+const memoryExtraction: MemoryExtractionModel = {
+  async extract(input) {
+    // Call your LLM here and return durable, objectivized facts.
+    return [
+      {
+        statement: 'The user started TypeScript in 2025.',
+        topics: ['user', 'TypeScript', '2025'],
+        confidence: 0.9,
+      },
+    ];
+  },
+};
+```
+
+Optional model hooks:
+
+- `models.initialization`: extracts initial persona facts from the seed message.
+- `models.rewrite`: decides whether to discard a stale draft if new messages arrived while generating.
+
+## 3. Create a persona
+
+```ts
+import { Persona } from 'boxbrain';
+
+const persona = new Persona(
+  'Mina',
+  'Mina is a careful student who likes quiet cafes and is preparing for exams.',
+  {
+    memory,
+    models: { conversation, memoryExtraction },
+    now: '2026-05-01T10:00:00.000Z',
+    debug: (event) => console.log(event),
+  },
+);
+
+const space = await persona.ready();
+console.log(space.id);
+```
+
+Creation behavior:
+
+- `new Persona(displayName, seedMessage, options)` creates a new isolated persona space.
+- The seed message is the freeform source for personality, history, likes, dislikes, relationships, and other persona facts.
+- If `models.initialization` is provided, BoxBrain asks it for initial facts.
+- If no initialization model is provided, BoxBrain stores a minimal seed fact.
+- If the initialization model intentionally returns an empty list, BoxBrain does not add the fallback fact.
+
+Load an existing persona:
+
+```ts
+const loaded = new Persona(space.id, { memory, models: { conversation, memoryExtraction } });
+await loaded.ready();
+```
+
+## 4. Generate schedules
+
+Create tomorrow's 10-minute schedule:
+
+```ts
+const entries = await persona.createDailySchedule(
+  '2026-05-01T10:00:00.000Z',
+  'Keep a normal work day.',
+);
+
+console.log(entries.length); // 144
+```
+
+Create a 30-day day-level outline, starting tomorrow:
+
+```ts
+await persona.createMonthlySchedule(
+  '2026-05-01T10:00:00.000Z',
+  'Mostly study, with occasional rest.',
+);
+```
+
+Current schedule generation is deterministic:
+
+- sleep before 07:00 and after 23:00
+- meal blocks around 07:00, 12:00, and 18:00
+- commute around 08:00 and 17:00
+- work/study/job-search/travel based on keywords in the message
+- rest/free-time in the evening
+
+## 5. Read availability
+
+```ts
+const availability = await persona.getTodayScheduledAvailability('2026-05-01T12:00:00.000Z');
+```
+
+The snapshot covers:
+
+- today 00:00
+- through tomorrow 24:00
+
+For example, if `datetime` is May 1, the window is May 1 00:00 through May 3 00:00.
+
+Availability is derived from schedule entries:
+
+- `sleep` -> `offline`
+- `work`, `study`, `job-search`, `travel`, `commute` -> `do-not-disturb`
+- `rest`, `meal`, `exercise`, `social`, `errand`, `free-time` -> `online`
+
+## 6. Reply to a user message
+
+```ts
+const reply = await persona.sendMessage({
+  datetime: '2026-05-01T12:00:00.000Z',
+  messageHistory: [
+    { sender: 'persona', time: '2026-04-30T23:00:00.000Z', content: 'See you later.' },
+    { sender: 'user', time: '2026-05-01T12:00:00.000Z', content: 'What are you doing?' },
+  ],
+});
+
+for (const message of reply.messages) {
+  await deliverToMessenger(message);
+}
+```
+
+BoxBrain formats the structured history for the model as:
+
+```text
+Mina@2026-04-30T23:00:00.000Z: See you later.
+user@2026-05-01T12:00:00.000Z: What are you doing?
+```
+
+## 7. Start a proactive conversation
+
+```ts
+const opener = await persona.startConversation({
+  datetime: '2026-05-01T20:00:00.000Z',
+  messageHistory: [],
+});
+```
+
+The same mandatory context pipeline is used, but the model input mode is `start-conversation`.
+
+## 8. Run sleep memory at midnight
+
+Recommended cadence: run once near midnight with the previous day's messages.
+
+```ts
+await persona.sleepMemory({
+  datetime: '2026-05-02T00:00:00.000Z',
+  messageHistory: messagesFromMay1,
+});
+```
+
+`sleepMemory` asks the memory extraction model to objectivize durable facts, then persists them to the persona's memory store.
+
+## 9. Add debug tracing
+
+```ts
+const persona = new Persona('Mina', seed, {
+  memory,
+  models,
+  debug(event) {
+    // Write to a log file, messenger admin channel, dashboard, etc.
+    console.log(`[${event.time}] ${event.name}`, event.data);
+  },
+});
+```
+
+Common debug events:
+
+- `persona.initialized`
+- `persona.loaded`
+- `persona.schedule.daily.generated`
+- `persona.schedule.monthly.generated`
+- `persona.schedule.deleted`
+- `persona.availability.refreshed`
+- `persona.conversation.context.loaded`
+- `persona.conversation.rewrite.checked`
+- `persona.conversation.reply.generated`
+- `persona.conversation.started`
+- `persona.memory.sleep.persisted`
diff --git a/Home.md b/Home.md
index e69de29..26ad53c 100644
--- a/Home.md
+++ b/Home.md
@@ -0,0 +1,89 @@
+# BoxBrain Wiki
+
+BoxBrain is a TypeScript framework for building LLM harnesses that make an AI-driven persona feel less like a generic assistant and more like a specific, continuing person.
+
+The framework is intentionally not a messenger bot, UI, or one-provider chatbot product. It supplies the core runtime primitives a host application needs:
+
+- isolated persona spaces backed by IdentityDB-compatible memory stores
+- persona initialization from a freeform seed message
+- realistic schedule entries and schedule-derived availability
+- reply and proactive conversation entry points
+- sleep-time memory extraction into durable facts
+- debug hooks for observing the framework flow and persona reasoning pipeline
+
+> Source of truth: this wiki is written against the current compact MVP source tree (`src/types.ts`, `src/memory.ts`, `src/schedule.ts`, `src/conversation.ts`, `src/persona.ts`, `src/index.ts`) at repository commit `49f75af`.
+
+## Why BoxBrain exists
+
+Most LLM chat integrations feel artificial because every response is generated in isolation: the model is always available, always has the same tone, and often pretends to remember things it has not actually loaded.
+
+BoxBrain exists to design the harness around the illusion of an ongoing person:
+
+1. **A persona has a private memory space.** Each persona is initialized into an isolated IdentityDB-style space. Facts about the persona, the user, their relationship, schedules, and durable memories live there.
+2. **A persona has time.** Schedules and availability make the persona online, busy, or offline depending on what they are supposed to be doing.
+3. **A persona can speak first.** `startConversation` supports proactive messages instead of only reactive replies.
+4. **A persona forgets unless memory is explicitly retrieved.** Mandatory memory retrieval tells the response model what was actually found; if nothing is found, the context explicitly says `기억이 없음`.
+5. **The host app controls delivery realism.** BoxBrain returns outgoing message drafts. The application should add typing indicators, status updates, delays, and delivery policy.
+
+## Current implementation status
+
+BoxBrain currently implements the framework core, not a complete human simulator.
+
+Implemented today:
+
+- `Persona` constructor overloads for creating/loading a persona space
+- `InMemoryMemoryStore`
+- `IdentityDbMemoryStore`
+- `createSqliteIdentityMemoryStore(filename)`
+- deterministic daily/monthly schedule helpers
+- schedule-derived availability snapshots
+- mandatory conversation context assembly
+- `sendMessage`, `startConversation`, and stale-draft rewrite checks
+- `sleepMemory` extraction pipeline
+- debug events
+
+Important current limitations:
+
+- Schedule generation is deterministic and rule-based in the current source, not yet an LLM-generated planner.
+- BoxBrain does not send messages itself. It returns `OutgoingMessageDraft.messages`; the host messenger integration must deliver them.
+- Typing indicators and typing delays are not built into the library yet. They should be implemented by the host app using the returned draft messages and availability snapshot.
+- The IdentityDB-backed store uses IdentityDB facts as its persistence layer. Schedule entries are stored in fact metadata. Because the public IdentityDB API is append-oriented, `IdentityDbMemoryStore.deleteScheduleEntriesBefore` currently returns `0`; the `Persona` layer records a deletion fact, while the in-memory store physically prunes entries.
+
+## Reading order
+
+1. [Getting Started](Getting-Started)
+2. [Human-Like Runtime Guide](Human-Like-Runtime)
+3. [API Reference](API-Reference)
+4. [Source Layout](Source-Layout)
+
+## Minimal example
+
+```ts
+import { Persona, createSqliteIdentityMemoryStore } from 'boxbrain';
+
+const memory = await createSqliteIdentityMemoryStore('.data/mina.sqlite');
+
+const persona = new Persona(
+  'Mina',
+  'Mina is a careful student who likes quiet cafes and is preparing for exams.',
+  {
+    memory,
+    models: {
+      conversation: yourConversationModel,
+      memoryExtraction: yourMemoryExtractionModel,
+    },
+    debug: (event) => console.log(event.name, event.data),
+  },
+);
+
+const space = await persona.ready();
+await persona.createDailySchedule(new Date(), 'Keep a normal study day.');
+
+const availability = await persona.getTodayScheduledAvailability(new Date());
+const reply = await persona.sendMessage({
+  datetime: new Date(),
+  messageHistory: [
+    { sender: 'user', time: new Date(), content: 'What are you doing?' },
+  ],
+});
+```
diff --git a/Human-Like-Runtime.md b/Human-Like-Runtime.md
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+++ b/Human-Like-Runtime.md
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+# Human-Like Runtime Guide
+
+BoxBrain's API is intentionally lower-level than a chatbot. It creates the reasoning and memory pipeline, while the host app controls messenger behavior: when to call the API, whether to show typing, how long to delay, and whether the persona should be available.
+
+This division is important. A real-person feeling comes from the whole runtime loop, not only from the LLM prompt.
+
+## The illusion stack
+
+A convincing persona usually needs all of these layers:
+
+1. **Persona identity** — stable display name, seed facts, personality, history, preferences, and relationships.
+2. **Durable memory** — IdentityDB-backed facts that can be retrieved instead of invented.
+3. **Recent conversation context** — yesterday/today messages passed by the API user as `messageHistory`.
+4. **Schedule** — ordinary days, work/study/rest/sleep, and occasional special events.
+5. **Availability/status** — `online`, `do-not-disturb`, or `offline` derived from schedule.
+6. **Delivery timing** — typing indicators, realistic delays, multi-message bursts, and deferral while offline.
+7. **Proactive behavior** — the persona sometimes starts conversations when schedule and relationship context make it plausible.
+8. **Sleep memory** — end-of-day summarization into objective durable facts.
+9. **Debug visibility** — trace hooks so developers can inspect why a persona did something.
+
+BoxBrain implements layers 1-5, 7's core conversation entry point, 8, and 9. The host app should implement delivery timing and product-specific policies.
+
+## Recommended daily loop
+
+Assume today is May 1.
+
+### On app startup
+
+1. Create or load the persona.
+2. Ensure yesterday/today/tomorrow schedules exist for the persona.
+3. Call `getTodayScheduledAvailability(now)` to rebuild the in-memory availability snapshot.
+4. Sync the host platform status from the snapshot.
+
+```ts
+const persona = new Persona(spaceId, { memory, models, debug });
+await persona.ready();
+const availability = await persona.getTodayScheduledAvailability(new Date());
+await updatePlatformPresence(availability);
+```
+
+The availability snapshot is stored in memory, not separately persisted. If the process restarts, loading the persona and calling `getTodayScheduledAvailability` rebuilds it from schedule entries in the memory store.
+
+### During the day
+
+- On inbound user messages, call `sendMessage`.
+- Before delivering replies, check current availability.
+- If `offline`, defer or suppress unless your product wants emergency replies.
+- If `do-not-disturb`, reply more slowly or only for high-priority messages.
+- If `online`, reply normally.
+- Periodically evaluate whether a proactive `startConversation` is appropriate.
+
+### Before midnight
+
+Generate tomorrow's 10-minute schedule:
+
+```ts
+await persona.createDailySchedule(now, 'Keep tomorrow realistic and ordinary.');
+```
+
+Because `createDailySchedule(datetime, message)` targets the day after `datetime`, running it on May 1 creates May 2 00:00 through May 3 00:00.
+
+### At midnight
+
+Run sleep memory on the previous day's messages:
+
+```ts
+await persona.sleepMemory({
+  datetime: '2026-05-02T00:00:00.000Z',
+  messageHistory: messagesFromMay1,
+});
+```
+
+Then drop local yesterday-only caches according to your application retention policy.
+
+## Message delivery policy
+
+`sendMessage` and `startConversation` return an `OutgoingMessageDraft`:
+
+```ts
+{
+  messages: ['I was studying.', 'Kinda sleepy now.'],
+  reasoning: 'optional model reasoning'
+}
+```
+
+BoxBrain does not call a messenger API. The host app should deliver each item in `messages` as one chat message.
+
+Recommended behavior:
+
+```ts
+for (const message of draft.messages) {
+  await messenger.showTyping(personaId);
+  await wait(typingDelayFor(message));
+  await messenger.sendMessage(channelId, message);
+  await wait(interMessagePause(message));
+}
+```
+
+A practical starting point:
+
+- typing delay: about `0.05` to `0.08` seconds per character
+- minimum delay: `600ms` to avoid instant bot-like replies
+- maximum delay: cap around `8-15s` unless the persona is intentionally slow
+- inter-message pause: `400-1500ms` between split messages
+
+Keep this deterministic-testable by injecting a random source or delay function in your host app.
+
+## One sentence per message
+
+The conversation instruction generated by BoxBrain tells the response model:
+
+- act as the persona, not a generic assistant
+- conceptually use a `send_message` tool
+- return one or more outgoing messages
+- unless the persona strongly prefers otherwise, keep each outgoing message to at most one sentence
+- prefer short, natural chat wording
+- split one thought across multiple messages when that feels human
+
+This is why `OutgoingMessageDraft.messages` is an array.
+
+## Availability-driven status
+
+`getTodayScheduledAvailability(datetime)` returns ranges like:
+
+```ts
+{
+  generatedAt: '2026-05-01T12:00:00.000Z',
+  windowStartAt: '2026-05-01T00:00:00.000Z',
+  windowEndAt: '2026-05-03T00:00:00.000Z',
+  ranges: [
+    {
+      startAt: '2026-05-02T00:00:00.000Z',
+      endAt: '2026-05-02T07:00:00.000Z',
+      mode: 'offline',
+      sourceScheduleIds: ['...'],
+      reason: 'Sleep'
+    }
+  ]
+}
+```
+
+Map it to platform presence like this:
+
+| BoxBrain mode | Messenger behavior | Suggested reply policy |
+| --- | --- | --- |
+| `online` | online/available | normal replies and proactive messages |
+| `do-not-disturb` | busy/DND/idle | slower replies, fewer proactive messages |
+| `offline` | offline/invisible | defer replies and suppress proactive messages |
+
+The current snapshot gives ranges, not a single `currentMode` helper. Host apps should compute the active range for `now`.
+
+## Proactive conversations
+
+`startConversation` lets the persona speak first:
+
+```ts
+const opener = await persona.startConversation({ datetime: now, messageHistory });
+```
+
+Recommended proactive gate:
+
+1. Compute active availability.
+2. Skip if `offline`.
+3. Strongly reduce probability if `do-not-disturb`.
+4. Check recent conversation cooldown.
+5. Check whether a schedule event makes the opener plausible.
+6. Call `startConversation`.
+7. Deliver with typing delay.
+
+Example policy:
+
+```ts
+if (active.mode === 'online' && minutesSinceLastMessage > 90) {
+  if (Math.random() < 0.08) {
+    const draft = await persona.startConversation({ datetime: now, messageHistory });
+    await deliverDraftWithTyping(draft);
+  }
+}
+```
+
+Good proactive openers usually refer to current context lightly instead of demanding attention:
+
+- after study/work: "I'm finally done for a bit."
+- during rest/free time: "It's weirdly quiet today."
+- around a known event: "I kept thinking about what you said yesterday."
+
+## Stale draft rewrite
+
+Real messaging is concurrent. A user may send another message while the model is generating a reply.
+
+`sendMessage` supports this through `getLatestMessageHistory` plus `models.rewrite`:
+
+```ts
+const reply = await persona.sendMessage({
+  datetime: now,
+  messageHistory: initialHistory,
+  getLatestMessageHistory: () => loadLatestMessagesFromMessenger(),
+});
+```
+
+If latest history has more messages than the original history, BoxBrain asks the rewrite model whether the draft should be discarded. If `rewrite: true`, BoxBrain uses the rewrite model's draft or regenerates with the latest context.
+
+Use this for:
+
+- corrections: "아 맞다..."
+- urgent additions: "wait, actually don't answer that"
+- rapid multi-message user input
+
+## Sleep memory and objectivization
+
+`sleepMemory` is the end-of-day memory pipeline.
+
+The memory extraction instruction tells the model to objectivize subjective statements before storage:
+
+```text
+"I started TypeScript in 2025" -> "The user started TypeScript in 2025."
+```
+
+Recommended extraction targets:
+
+- durable user facts
+- persona facts
+- preferences and dislikes
+- relationship facts
+- stable history
+- schedule-relevant future events
+- recurring emotional context
+
+Avoid storing:
+
+- transient small talk
+- one-off jokes with no future use
+- raw message dumps
+- facts contradicted by the current conversation unless the model explains the update
+
+## Debug hooks for observability
+
+Use `debug(event)` to make the invisible harness visible:
+
+```ts
+debug(event) {
+  trace.write({
+    name: event.name,
+    time: event.time,
+    spaceId: event.spaceId,
+    data: event.data,
+  });
+}
+```
+
+Recommended debug sinks:
+
+- local JSONL trace file
+- admin dashboard
+- developer-only messenger channel
+- test snapshots
+
+Useful event groups:
+
+- initialization: `persona.initialized`, `persona.loaded`
+- schedule/status: `persona.schedule.daily.generated`, `persona.schedule.monthly.generated`, `persona.schedule.deleted`, `persona.availability.refreshed`
+- conversation: `persona.conversation.context.loaded`, `persona.conversation.rewrite.checked`, `persona.conversation.reply.generated`, `persona.conversation.started`
+- memory: `persona.memory.sleep.persisted`
+
+## What not to fake
+
+To preserve trust in the harness, do not make the model pretend it knows unavailable information.
+
+BoxBrain already helps here: when mandatory persona/user memory lookup returns no facts, the context says `기억이 없음`. Let the persona react naturally:
+
+- "I don't think I know that yet."
+- "Did you tell me before?"
+- "I might be missing that memory."
+
+That is usually more human than a confident hallucination.
diff --git a/Source-Layout.md b/Source-Layout.md
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+# Source Layout
+
+BoxBrain's current implementation is intentionally compact. The repository focuses on a framework core rather than a full chatbot product.
+
+## Root files
+
+| Path | Purpose |
+| --- | --- |
+| `README.md` | High-level project overview and quick API examples |
+| `package.json` | Package metadata, Bun scripts, runtime dependencies |
+| `tsconfig.json` | TypeScript configuration |
+| `bun.lock` | Bun lockfile |
+| `.gitea/workflows/ci.yml` | Gitea CI workflow |
+
+## Source files
+
+| Path | Purpose |
+| --- | --- |
+| `src/index.ts` | Root barrel export for public APIs |
+| `src/types.ts` | Public TypeScript contracts: memory, schedules, models, messages, debug events |
+| `src/memory.ts` | `InMemoryMemoryStore`, `IdentityDbMemoryStore`, SQLite helper |
+| `src/schedule.ts` | Datetime helpers, deterministic schedule generation, availability derivation |
+| `src/conversation.ts` | Message-history formatting, prompts/instructions, mandatory context assembly |
+| `src/persona.ts` | Main `Persona` class and orchestration pipeline |
+
+## Tests
+
+| Path | Covered behavior |
+| --- | --- |
+| `tests/persona.test.ts` | persona creation/loading, initialization facts, debug events |
+| `tests/schedule.test.ts` | daily schedule generation, availability, pruning |
+| `tests/conversation.test.ts` | mandatory context, missing memory marker, stale rewrite, proactive opener |
+| `tests/sleep-memory.test.ts` | objectivized memory extraction and persistence |
+| `tests/memory.test.ts` | fact listing for in-memory and SQLite IdentityDB stores |
+
+## Public export shape
+
+`src/index.ts` exports everything from:
+
+```ts
+export * from './types';
+export * from './memory';
+export * from './schedule';
+export * from './conversation';
+export * from './persona';
+```
+
+This means consumers can import framework types and helper functions from `boxbrain` directly.
+
+## Implementation notes
+
+### Persona initialization
+
+`src/persona.ts` provides constructor overloads:
+
+```ts
+new Persona(displayName, seedMessage, options)
+new Persona(spaceId, options)
+```
+
+Create mode stores a new memory space. Load mode retrieves an existing space. `ready()` awaits the initialization promise.
+
+### Memory storage
+
+`src/memory.ts` has two concrete stores:
+
+- `InMemoryMemoryStore` for tests/demos
+- `IdentityDbMemoryStore` for persistent IdentityDB-backed spaces
+
+Schedule entries in the IdentityDB store are saved as facts with `metadata.scheduleEntry`.
+
+### Schedule and availability
+
+`src/schedule.ts` currently uses a deterministic routine:
+
+- 144 ten-minute blocks for a daily schedule
+- 30 day-level entries for monthly schedules
+- keyword-based activity choice for work/study/job-search/travel
+- availability ranges derived from schedule activity metadata
+
+### Conversation context
+
+`src/conversation.ts` centralizes mandatory context:
+
+- formatted message history
+- yesterday/today/tomorrow schedule lookup
+- persona/user fact lookup
+- `기억이 없음` marker when no mandatory memory is found
+- schedule-derived availability snapshot
+
+### Persona orchestration
+
+`src/persona.ts` ties the pieces together:
+
+- schedule creation and pruning
+- availability refresh/cache
+- reply generation
+- proactive conversation start
+- stale-draft rewrite checks
+- sleep-memory persistence
+- debug event emission
+
+## Verification commands
+
+From the repository root:
+
+```bash
+bun install
+bun run test
+bun run check
+bun run build
+```
diff --git a/_Sidebar.md b/_Sidebar.md
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+# BoxBrain Wiki
+
+- [Home](Home)
+- [Getting Started](Getting-Started)
+- [Human-Like Runtime Guide](Human-Like-Runtime)
+- [API Reference](API-Reference)
+- [Source Layout](Source-Layout)