## ADDED Requirements

### Requirement: Fact extraction from conversation
The system SHALL extract structured facts from conversations using an LLM, with confidence scoring and category classification.

#### Scenario: Extract facts from conversation turn
- **WHEN** a conversation turn (user message + assistant reply) is processed
- **THEN** the system SHALL call the configured LLM with the conversation text
- **THEN** the LLM response SHALL be parsed as structured JSON with facts
- **THEN** each fact SHALL contain: `content`, `category`, `confidence` (0.0-1.0)

#### Scenario: Fact categories
- **WHEN** a fact is extracted
- **THEN** its `category` SHALL be one of: `preference`, `knowledge`, `context`, `behavior`, `goal`, `correction`
- **THEN** the system SHALL validate the category against the allowed set

#### Scenario: Confidence thresholds
- **WHEN** a fact's confidence is below the configurable threshold (default 0.5)
- **THEN** the fact SHALL NOT be persisted
- **THEN** the system SHALL log that a low-confidence fact was skipped

### Requirement: Fact CRUD operations
The system SHALL support creating, reading, updating, and deleting memory facts.

#### Scenario: Create fact
- **WHEN** a new fact is created
- **THEN** it SHALL be assigned a unique ID (`fact_{uuid_hex[:8]}`)
- **THEN** it SHALL be timestamped with ISO-8601 UTC
- **THEN** it SHALL be persisted to the core store

#### Scenario: Delete fact by ID
- **WHEN** a fact deletion is requested with a valid ID
- **THEN** the fact SHALL be removed from the store
- **THEN** the updated store SHALL be persisted

#### Scenario: Delete non-existent fact
- **WHEN** a fact deletion is requested with an unknown ID
- **THEN** the system SHALL raise `KeyError`

#### Scenario: Update fact
- **WHEN** a fact update is requested with a valid ID
- **THEN** the system SHALL update only the provided fields (`content`, `category`, `confidence`)
- **THEN** the fact's `createdAt` SHALL NOT be modified
- **THEN** the updated store SHALL be persisted

### Requirement: Content deduplication
The system SHALL prevent duplicate facts by casefolded content comparison.

#### Scenario: Exact duplicate detected
- **WHEN** a new fact's content (casefolded) matches an existing fact
- **THEN** the new fact SHALL be skipped
- **THEN** the existing fact SHALL remain unchanged
- **THEN** the system SHALL log that a duplicate was skipped

#### Scenario: Near-duplicate with different casing
- **WHEN** a new fact's content differs only in letter casing
- **THEN** it SHALL be treated as a duplicate
- **THEN** the new fact SHALL be skipped

### Requirement: Max facts limit
The system SHALL enforce a configurable maximum number of stored facts (default 500).

#### Scenario: Fact count exceeds limit
- **WHEN** adding a new fact would exceed `max_facts`
- **THEN** the system SHALL sort existing facts by confidence (descending)
- **THEN** the lowest-confidence fact SHALL be removed
- **THEN** the new fact SHALL be added

### Requirement: Memory formatting for context injection
The system SHALL format memory data into a compact string for injection into LLM system prompts, respecting a token budget.

#### Scenario: Format with all sections
- **WHEN** memory data contains user context, history, and facts
- **THEN** the output SHALL include: "User Context:" with work/personal/topOfMind
- **THEN** the output SHALL include: "History:" with recent/earlier/background
- **THEN** the output SHALL include: "Facts:" sorted by confidence descending
- **THEN** each fact SHALL be formatted as: `- [{category} | {confidence:.2f}] {content}`

#### Scenario: Token budget enforcement
- **WHEN** the formatted output exceeds `max_tokens` (default 2000)
- **THEN** the system SHALL trim facts from lowest confidence up
- **THEN** if still over budget, the output SHALL be truncated at the character level
- **THEN** `"\n..."` SHALL be appended to indicate truncation