boocode/openspec/changes/archived/2026-06-07-memory-context-engineering/specs/long-term-memory/spec.md at c11e26090fe2ca984cd54fecb147700e3773cfa3

Files

indifferentketchup c935687725 chore(openspec): drop 9 superseded proposals + 11 stub archive files

Drop 9 batch proposals that are superseded by the boocode-lift-analysis
(boocontext-audit, conductor upgrades, self-healing/verify-gate skills):
add-3tier-memory, import-llm-evaluator, import-pregel-engine, plugin-platform,
conductor-evolution, code-intelligence-upgrade, dev-workflow, ui-overhaul,
agent-reliability.

Delete 11 stub archive files (49-66B each, 'Status: Shipped. Archived.' only)
that provide zero documentation value over the existing CHANGELOG.md + git tags.

2026-06-07 22:15:38 +00:00

3.8 KiB

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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

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