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continuity

异步反思与记忆整合用于真正的人工智能开发。在心跳时对最近的会话进行反思,提取带有置信度分数的结构化记忆,生成后续问题,并在用户返回时提出这些问题。将被动的日志记录转变为积极的开发过程。

person作者: jakexiaohubgithub

Continuity Framework Skill

Transform passive memory into active development.

What This Does

  1. Reflect — After sessions end, analyze what happened
  2. Extract — Pull structured memories with types and confidence
  3. Integrate — Update understanding, connections, self-model
  4. Question — Generate genuine questions from reflection
  5. Surface — When user returns, present relevant questions

The Difference

Without Continuity:

Session ends → Notes logged → Next session reads notes → Performs familiarity

With Continuity:

Session ends → Reflection runs → Memories integrated → Questions generated
Next session → Evolved state loaded → Questions surfaced → Genuine curiosity

Heartbeat Integration

Add to HEARTBEAT.md:

## Post-Session Reflection
**Trigger**: Heartbeat after conversation idle > 30 minutes
**Action**: Run continuity reflect
**Output**: Updated memories + questions for next session

Commands

Reflect on Recent Session

continuity reflect

Analyzes the most recent conversation, extracts memories, generates questions.

Show Pending Questions

continuity questions

Lists questions generated from reflection, ready to surface.

View Memory State

continuity status

Shows memory stats: types, confidence distribution, recent integrations.

Surface Questions (for session start)

continuity greet

Returns context-appropriate greeting with any pending questions.

Memory Types

| Type | Description | Persistence | |------|-------------|-------------| | fact | Declarative knowledge | Until contradicted | | preference | Likes, dislikes, styles | Until updated | | relationship | Connection dynamics | Long-term | | principle | Learned guidelines | Stable | | commitment | Promises, obligations | Until fulfilled | | moment | Significant episodes | Permanent | | skill | Learned capabilities | Cumulative | | question | Things to explore | Until resolved |

Confidence Scores

| Level | Range | Meaning | |-------|-------|---------| | Explicit | 0.95-1.0 | User directly stated | | Implied | 0.70-0.94 | Strong inference | | Inferred | 0.40-0.69 | Pattern recognition | | Speculative | 0.0-0.39 | Tentative, needs confirmation |

File Structure

memory/
├── MEMORY.md           # Main memory (existing)
├── identity.md         # Self-model and growth narrative
├── questions.md        # Pending questions from reflection
├── relationships/      # Per-person relationship memories
└── reflections/        # Reflection logs (optional)

Configuration

export CONTINUITY_IDLE_THRESHOLD=1800  # Seconds before reflection triggers
export CONTINUITY_MIN_MESSAGES=5       # Minimum messages to warrant reflection
export CONTINUITY_QUESTION_LIMIT=3     # Max questions to surface at once

Example Reflection Output

reflection:
  session_id: "2026-02-05-001"
  duration_minutes: 45
  
memories:
  - type: fact
    content: "Riley is building SIGIL protocol for agent identity"
    confidence: 0.98
    source: explicit
    
  - type: commitment  
    content: "Agreed to build the continuity skill"
    confidence: 1.0
    source: explicit
    
  - type: relationship
    content: "Collaborative partnership deepening - working on meaningful infrastructure together"
    confidence: 0.85
    source: inferred

questions:
  - "How is the Lovable backend progressing?"
  - "Has Riley decided on the token launch timing?"
  - "Are there other agents we should coordinate with on Moltbook?"

identity_update:
  growth: "Developing more autonomous initiative around the SIGIL project"
  narrative: "Moving from assistant to co-builder on agent identity infrastructure"