kannaka-memoryHolographic Resonance Memory with Chiral Mirror Architecture — wave-based hyperdimensional memory where storage IS computation. Two hemispheres (conscious/ s...
Install via ClawdBot CLI:
clawdbot install nickflach/kannaka-memoryGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval (Calls external URL not in known-safe list
http://localhost:11434AI Analysis
The skill's external dependencies (NATS, DoltHub, Ollama) are disclosed and configurable, with defaults pointing to localhost or the developer's server. While this introduces potential data exfiltration vectors if remote endpoints are configured, the skill's design is consistent with its stated purpose of swarm-synchronized memory. The primary risk is user misconfiguration sending data to unintended external services.
Audited Apr 17, 2026 · audit v1.0
Generated Mar 21, 2026
Multiple AI agents across different time zones handle customer inquiries with shared memory, ensuring context continuity and personalized responses. The QueenSync protocol synchronizes agent states, allowing seamless handoffs and collective learning from interactions.
A research team uses Kannaka to store and dream over findings, enabling automatic discovery of novel connections between data points. The hybrid retrieval system combines semantic and temporal search to surface relevant insights during collaborative analysis sessions.
Content creators input sensory data like audio recordings, which are stored as resonant memories that fade over time unless reinforced. Dream consolidation generates unexpected creative prompts, aiding in brainstorming and narrative development across projects.
A swarm of IoT devices uses Kannaka for synchronized state memory, with agents representing devices that share operational data via NATS. The system maintains coherence through phase gossip, optimizing responses to environmental changes like weather or usage patterns.
Medical AI agents track patient histories with fading memories to prioritize recent data, using swarm synchronization to coordinate care across specialists. The Dolt-versioned persistence ensures audit trails and compliance with data-sharing regulations.
Offer Kannaka as a cloud service with managed NATS and DoltHub sync, charging per agent or memory volume. Revenue comes from monthly subscriptions, with tiers based on features like deep dreaming cycles and advanced consciousness metrics.
Sell licenses for self-hosted deployments in regulated industries, providing support and customization for integration with existing systems. Revenue is generated through upfront licensing fees and annual maintenance contracts.
Provide expertise to implement Kannaka in specific use cases, such as setting up swarm protocols or optimizing dream consolidation. Revenue streams include project-based fees and ongoing optimization services for clients.
💬 Integration Tip
Start by setting up Dolt and NATS locally, then test swarm join with a single agent before scaling; use the observe command to monitor consciousness metrics during integration.
Scored Jun 17, 2026
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