continuity
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.
What this skill does
# 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:
```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
| 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
```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"
```
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