Memory Harness

A reliable memory harness that makes byterover recall happen at the right times without running heavy recall on every turn.

Architecture

user_input
  -> intent classification
  -> session preflight (if new session)
  -> conditional targeted recall
  -> planning
  -> pre-execution recall gate (if execution-like)
  -> execution or response
  -> optional writeback

3-Stage Harness

Stage 1: Session Preflight

Runs ONLY at the start of a new session.

Fetches: - active project - pinned facts - unresolved items - recent important entities - recent session summary

Does NOT fetch: - full raw history - large raw memory dumps - low-signal old notes

Output: compact session_digest (hard capped)

Stage 2: Triggered Recall

Runs targeted byterover recall only when needed.

Trigger conditions: - Continuation words: 続き, 前回, 再開, 引き継ぎ, continue, resume, previous work - Known entity/project name: ClawHub, OpenClaw, Agent-OS, BOSS-memory-loop, etc. - Task requires user-specific/project-specific context - Implementation / modification / design / planning request - Ambiguous task likely depending on prior context

Skip conditions: - Generic factual Q&A - Small self-contained questions - Casual short exchange - Clearly answerable without prior context

Recall modes: - preflight_query: start-of-session only - entity_query: when named entities detected - continuation_query: for previous-session continuation - constraint_query: when advice depends on prior rules - pre_execution_query: immediately before execution

Stage 3: Pre-Execution Recall Gate

MANDATORY before: - file edits - code generation - architecture proposals - configuration changes - planning depending on prior project state - any meaningful change suggestion

Checks for: - prior constraints - unresolved issues - conflicting past decisions - project-specific conventions - safety-sensitive context

Memory Shaping

Never inject raw byterover results directly.

Pipeline: 1. retrieve 2. rank 3. dedupe 4. compress 5. inject bounded digest

Hard limits: - max_memory_items: 5 - max_digest_lines: 8 - prefer recent + high-signal + tagged items

Status Tracking

Every recall records one of: - not_needed - queried_no_hits - queried_low_confidence - queried_success - query_failed

Scripts

intent-classifier.js

Classifies turn intent as one of: - generic_qa - casual - continuation - entity_reference - user_specific_context - implementation_request - design_request - execution_request

entity-detector.js

Detects known entities in user input: - Scans for known entity/project names - Maps aliases to canonical names - Returns matched entities for recall routing

session-preflight.sh

Runs lightweight recall at session start: - Fetches pinned facts, active project, unresolved items - Creates compact session_digest - Hard capped length

targeted-recall.sh

Runs targeted recall based on intent: - Takes intent, entities, session state - Chooses appropriate recall mode - Returns compressed digest

pre-execution-gate.sh

Runs before execution-like actions: - Checks for constraints, conflicts, safety issues - Returns go/no-go with relevant context

memory-compress.js

Compresses and dedupes raw memory: - Ranks by relevance and recency - Dedupes repeated items - Hard caps output size

writeback.sh

Writes high-signal info back to memory: - Only for important decisions/outcomes - Skips trivial chat and low-value text

Configuration

{
  "memory_policy": {
    "preflight_on_session_start": true,
    "preflight_depth": "light",
    "pre_execution_recall": true,
    "max_memory_items": 5,
    "max_digest_lines": 8,
    "trigger_query_if": [
      "mentions_known_project",
      "asks_to_continue_previous_work",
      "requires_user_specific_context",
      "requests_code_design_or_change",
      "contains_known_entity"
    ],
    "skip_query_if": [
      "generic_qa",
      "casual_chat",
      "self_contained_question"
    ]
  }
}

Logging

Structured logs for observability: - turn_id - session_id - intent - recall_trigger - recall_mode - recall_status - recall_item_count - injected_item_count - pre_execution_gate - elapsed_ms

Known Entities

Default entity list (expandable): - ClawHub - OpenClaw - Agent-OS - BOSS-memory-loop - ByteRover - MISO - Obsidian - Telegram

Continuation Triggers

Japanese: 続き, 前回, 再開, 引き継ぎ, 前の, さっきの English: continue, resume, previous, earlier, last time, back to

Success Criteria

• Reliable recall when turn depends on context
• Generic turns stay lightweight
• Execution actions always get constraint check
• Behavior inspectable in logs
• No reliance on SKILL.md text alone