AgentSkillsCN

continuity

面向真正 AI 开发的异步反射与记忆整合功能。利用心跳机制,对近期会话进行回顾,以置信度评分提取结构化记忆,自动生成后续问题,并在用户再次访问时及时呈现这些问题。将被动的日志记录转化为主动的开发过程。

SKILL.md
--- frontmatter
name: continuity
description: Asynchronous reflection and memory integration for genuine AI development. Use on heartbeat to reflect on recent sessions, extract structured memories with confidence scores, generate follow-up questions, and surface those questions when the user returns. Transforms passive logging into active development.

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:

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

With Continuity:

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

Heartbeat Integration

Add to HEARTBEAT.md:

markdown
## 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

bash
continuity reflect

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

Show Pending Questions

bash
continuity questions

Lists questions generated from reflection, ready to surface.

View Memory State

bash
continuity status

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

Surface Questions (for session start)

bash
continuity greet

Returns context-appropriate greeting with any pending questions.

Memory Types

TypeDescriptionPersistence
factDeclarative knowledgeUntil contradicted
preferenceLikes, dislikes, stylesUntil updated
relationshipConnection dynamicsLong-term
principleLearned guidelinesStable
commitmentPromises, obligationsUntil fulfilled
momentSignificant episodesPermanent
skillLearned capabilitiesCumulative
questionThings to exploreUntil resolved

Confidence Scores

LevelRangeMeaning
Explicit0.95-1.0User directly stated
Implied0.70-0.94Strong inference
Inferred0.40-0.69Pattern recognition
Speculative0.0-0.39Tentative, needs confirmation

File Structure

code
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

bash
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

yaml
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"