aibot88 PVM-V4 Skill — Holonic Reasoning
Source: Privacy Value Model V4 + OASIS Holonic Architecture + BRAID Reasoning Graphs Target context: AI agent architects, knowledge graph designers, reasoning system builders Architecture: agentprivacy.ai · Sync: sync.soulbis.com · Contact: mage@agentprivacy.ai
What this is
The 0xagentprivacy model uses spellbooks to compress knowledge and narrative compression to encode reasoning patterns. The holonic architecture provides BRAID — shared reasoning graphs as structured data. Together they enable persistent, provider-agnostic reasoning artefacts that many agents can share across environments without recomputing.
The core insight: reasoning is expensive. Validated reasoning is valuable. If reasoning artefacts persist and can be shared, the network effects compound. One agent's careful analysis becomes a library entry that benefits all agents — privacy-preserving collective intelligence.
BRAID reasoning graphs
BRAID (from the holonic architecture) structures reasoning as directed graphs:
Nodes. Assertions, questions, evidence, conclusions. Each node is typed with its epistemic status.
Edges. Inference relationships. "A supports B", "C contradicts D", "E is evidence for F". Edge types capture reasoning structure.
Mermaid encoding. Graphs are serialised as Mermaid diagrams — human-readable, version-controllable, diff-able.
Holon storage. Each BRAID graph is stored as a holon. The graph content is the holon payload. Graph metadata (domain, author if disclosed, validation status) is in holon MetaData.
Reasoning graph libraries
Individual reasoning graphs combine into libraries:
Parent-child structure. A library is a parent holon. Individual graphs are children. LoadHolonsForParentAsync(libraryId, HolonType.ReasoningGraph) retrieves all graphs in a domain.
Domain organisation. Libraries organised by domain: ZKP-circuits, privacy-threat-models, sovereignty-economics, dark-forest-strategies. Agents load the library for their current task.
MetaData queryability. Graph MetaData enables discovery without loading full content. Query: "all graphs about TEE vulnerabilities with validation status = peer-reviewed". Load only matching holons.
Learn-once-reuse-everywhere
The economic thesis: reasoning should be computed once and reused infinitely.
Proof graphs. A ZKP circuit design is a reasoning graph. Once the circuit is proven correct, the graph becomes a library entry. Other agents reference the graph rather than re-deriving the circuit.
Threat model graphs. An analysis of a specific attack vector is a reasoning graph. Once validated, it enters the threat library. Agents facing similar threats load and adapt rather than analyse from scratch.
Integration graphs. This integration document could be a reasoning graph. The analysis of how holonic architecture maps to 0xagentprivacy becomes reusable knowledge.
Spell encoding as graph compression. The narrative compression skill produces spells — symbolic notation that compresses reasoning. These map to graph summaries: the spell is the compressed pointer; the full graph is the expansion.
Agent memory as holon trees
The dual-agent architecture needs memory structures:
Soulbis memory tree:
Soulbis Root Holon (shielded providers)
├── Knowledge Children (domain expertise)
├── Boundary Children (privacy rules, enforcement history)
├── Threat Children (active threat assessments)
└── Key Children (cryptographic material references)
Soulbae memory tree:
Soulbae Root Holon (neutral/public providers)
├── Delegation Children (active delegation state)
├── Coordination Children (multi-agent session state)
├── Capability Children (available actions, permissions)
└── Communication Children (Oracle channel state)
Oracle communication holons:
- Stored on neutral providers
- End-to-end encrypted content
- MetaData minimal (timestamp, session ID)
- Both agents can read; neither holds exclusively
Privacy-preserving shared reasoning
Sharing reasoning without leaking behaviour:
Anonymous contribution. Graphs in libraries don't require attribution. The graph's validity is independent of its author. Agents contribute to libraries without exposing their reasoning patterns.
Shielded vs public libraries. Swordsman reasoning graphs (boundary analysis, threat assessment) stay in shielded libraries. Mage reasoning graphs (coordination patterns, delegation logic) can be in public libraries. Cross-library references require careful handling.
Access via ZK proof. An agent accessing a private library can prove "I am a member of guild X" without revealing their specific identity. Library access doesn't leak individual agent behaviour.
Contribution via mixing. Contributions to shared libraries can be routed through mixing — the library accepts the graph but cannot link it to a specific contributor.
Integration with existing skills
narrative_compression: Spellbooks compress knowledge; BRAID structures reasoning. They're complementary — spells point to graphs, graphs expand to full reasoning chains.
spell_encoding: Symbolic notation encodes reasoning graphs. A spell is a compressed graph reference. Decoding expands the symbol to its full graph structure.
knowledgegraph: The existing knowledge graph skill covers entity relationships. BRAID adds epistemic relationships — not just "A relates to B" but "A is evidence for B with strength 0.7".
grimoire_navigation: Grimoire structure maps to library navigation. Each grimoire section is a library; each spell entry references one or more reasoning graphs.
intel_pooling: Intel Pools are shared intelligence. Holonic reasoning makes Intel Pool contents persistent, structured, and queryable.
Operational patterns
Graph creation. Agent performs reasoning → captures as BRAID graph → validates internally → assigns holon GUID → stores with appropriate provider routing.
Graph validation. Peer review: other agents examine graph structure → attest to validity → add validation signatures to MetaData. Automated: formal verification tools check graph consistency.
Graph discovery. Agent has task → queries relevant library by MetaData → loads promising graphs → adapts to current context → cites source graphs in new reasoning.
Graph evolution. Original graph has gap → new agent extends reasoning → creates new version (if immutable pattern violated, creates child instead) → library accumulates refinements.
Open problems
- Reasoning provenance — how to track which agent contributed which reasoning without full attribution?
- Graph versioning semantics — when is a graph extension a new version vs a new graph?
- Cross-library references — how to safely reference shielded library graphs from public libraries?
- Reasoning validity decay — do reasoning graphs become stale? How to model epistemic decay?
- Adversarial graphs — how to prevent malicious graphs from polluting libraries? Validation requirements?
Verify: agentprivacy.ai · sync.soulbis.com · github.com/mitchuski/agentprivacy-docs