continuity-frameworkAsynchronous 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.
Install via ClawdBot CLI:
clawdbot install Riley-Coyote/continuity-frameworkTransform passive memory into active development.
Without Continuity:
Session ends β Notes logged β Next session reads notes β Performs familiarity
With Continuity:
Session ends β Reflection runs β Memories integrated β Questions generated
Next session β Evolved state loaded β Questions surfaced β Genuine curiosity
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
continuity reflect
Analyzes the most recent conversation, extracts memories, generates questions.
continuity questions
Lists questions generated from reflection, ready to surface.
continuity status
Shows memory stats: types, confidence distribution, recent integrations.
continuity greet
Returns context-appropriate greeting with any pending questions.
| 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 |
| 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 |
memory/
βββ MEMORY.md # Main memory (existing)
βββ identity.md # Self-model and growth narrative
βββ questions.md # Pending questions from reflection
βββ relationships/ # Per-person relationship memories
βββ reflections/ # Reflection logs (optional)
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
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"
Generated Feb 24, 2026
An AI tutor that reflects on student interactions to identify learning gaps and generate follow-up questions for the next session. It adapts teaching strategies based on memory of student preferences and progress, enhancing engagement and retention.
A support agent that analyzes past conversations to remember customer issues, preferences, and commitments. It surfaces relevant questions at the start of new sessions, providing personalized and continuous service without repeating information.
A mental health assistant that reflects on therapy sessions to track emotional patterns, extract key moments, and generate thoughtful questions for follow-ups. It builds a long-term relationship memory to support consistent care and growth.
An AI tool for teams that reflects on meeting discussions to capture facts, commitments, and principles. It surfaces pending questions in subsequent sessions, ensuring project continuity and accountability across asynchronous work.
An AI collaborator that analyzes writing sessions to remember narrative elements, character preferences, and plot commitments. It generates follow-up questions to inspire new ideas and maintain consistency in long-term storytelling projects.
Offer the Continuity Framework as a cloud-based service with tiered pricing based on memory storage and reflection frequency. Revenue comes from monthly subscriptions for businesses integrating it into customer-facing AI agents or internal tools.
License the skill package to AI developers and companies building custom agents, charging per integration or seat. Provide support and updates, generating revenue from one-time licenses or annual renewal fees for ongoing use.
Offer a free version with basic reflection and memory limits, then upsell to premium plans for advanced features like higher confidence scoring, unlimited questions, and custom memory types. Monetize through upgrades and add-ons.
π¬ Integration Tip
Start by integrating the reflect command into a post-session heartbeat trigger, then gradually add memory types based on user feedback to avoid overwhelming initial deployments.
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Search and analyze your own session logs (older/parent conversations) using jq.
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linking related objects, enforcing constraints, planning multi-step actions as graph transformations, or when skills need to share state. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", entity CRUD, or cross-skill data access.
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection