Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Continuity Framework
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.
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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.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/framework.md, scripts/continuity.py
Validation
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- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
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New install
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- Riley-Coyote
- Source page
- View original listing
- Canonical URL
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Documentation
Continuity Framework Skill
Transform passive memory into active development.
What This Does
Reflect β After sessions end, analyze what happened Extract β Pull structured memories with types and confidence Integrate β Update understanding, connections, self-model Question β Generate genuine questions from reflection Surface β When user returns, present relevant questions
The Difference
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
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
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
TypeDescriptionPersistencefactDeclarative knowledgeUntil contradictedpreferenceLikes, dislikes, stylesUntil updatedrelationshipConnection dynamicsLong-termprincipleLearned guidelinesStablecommitmentPromises, obligationsUntil fulfilledmomentSignificant episodesPermanentskillLearned capabilitiesCumulativequestionThings to exploreUntil resolved
Confidence Scores
LevelRangeMeaningExplicit0.95-1.0User directly statedImplied0.70-0.94Strong inferenceInferred0.40-0.69Pattern recognitionSpeculative0.0-0.39Tentative, needs confirmation
File Structure
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)
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"
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- references/framework.md
- scripts/continuity.py