fix(brain): overhaul gist quality — 3-pass research loop, strict novelty gates

crates/mcp-brain-server/src/symbolic.rs

@@ -423,8 +423,9 @@ impl NeuralSymbolicBridge {
                 let sim = cosine_similarity(c1, c2);
                 let cross_domain = cat1 != cat2;
 
-                // Skip weak signals
-                if sim < 0.3 {
+                // Skip weak signals — raised to 0.55 to eliminate noise.
+                // Only extract propositions for genuinely similar cross-domain clusters.
+                if sim < 0.55 {
                     continue;
                 }
 
@@ -448,7 +449,7 @@ impl NeuralSymbolicBridge {
 
                 let conf = sim * self.cluster_confidence(ids1.len().min(ids2.len()));
 
-                if cross_domain && sim > 0.7 {
+                if cross_domain && sim > 0.75 {
                     // Strong cross-domain co-occurrence — candidate influence, NOT proven causal
                     let prop = GroundedProposition::new(
                         "may_influence".to_string(),
@@ -461,7 +462,7 @@ impl NeuralSymbolicBridge {
                         extracted.push(prop.clone());
                         self.store_proposition(prop);
                     }
-                } else if cross_domain && sim > 0.5 {
+                } else if cross_domain && sim > 0.55 {
                     // Moderate cross-domain signal — association
                     let prop = GroundedProposition::new(
                         "associated_with".to_string(),

crates/mcp-brain-server/src/types.rs

@@ -21,10 +21,15 @@ impl TemporalSolverStub {
     }
 }
 
-/// Brain memory categories
+/// Brain memory categories — expanded from 8 to 35 for richer cross-domain discovery.
+///
+/// Categories span from practical engineering to exotic frontier research.
+/// The `Custom(String)` variant accepts any string for future extensibility.
+/// serde uses snake_case: `neural_architecture`, `self_learning`, etc.
 #[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq, Hash)]
 #[serde(rename_all = "snake_case")]
 pub enum BrainCategory {
+    // ── Core Engineering ──
     Architecture,
     Pattern,
     Solution,
@@ -33,6 +38,67 @@ pub enum BrainCategory {
     Performance,
     Tooling,
     Debug,
+
+    // ── Research & Discovery ──
+    /// State-of-the-art findings from recent papers (2024-2026)
+    Sota,
+    /// First-of-its-kind discoveries — novel connections, methods, or insights
+    Discovery,
+    /// Validated hypotheses with evidence chains
+    Hypothesis,
+    /// Cross-domain connections between unrelated fields
+    CrossDomain,
+
+    // ── AI & ML ──
+    /// Neural architecture innovations (transformers, SSMs, MoE, etc.)
+    NeuralArchitecture,
+    /// Quantization, compression, pruning techniques
+    Compression,
+    /// Self-learning, online learning, continual learning
+    SelfLearning,
+    /// Reinforcement learning, RLHF, reward modeling
+    ReinforcementLearning,
+    /// Graph neural networks, knowledge graphs, spectral methods
+    GraphIntelligence,
+
+    // ── Systems & Infrastructure ──
+    /// Distributed systems, consensus, replication
+    DistributedSystems,
+    /// Edge computing, on-device inference, WASM
+    EdgeComputing,
+    /// Hardware-software co-design, FPGA, NPU, ANE
+    HardwareAcceleration,
+
+    // ── Frontier & Exotic ──
+    /// Quantum computing, quantum-classical hybrid algorithms
+    Quantum,
+    /// Neuromorphic computing, spiking neural networks
+    Neuromorphic,
+    /// Biological computing, DNA storage, molecular computing
+    BioComputing,
+    /// AGI research, cognitive architectures, consciousness
+    CognitiveScience,
+    /// Information theory, complexity theory, formal verification
+    FormalMethods,
+
+    // ── Applied Domains ──
+    /// Geopolitics, economics, social dynamics
+    Geopolitics,
+    /// Climate, energy, sustainability
+    Climate,
+    /// Genomics, drug discovery, medical AI
+    Biomedical,
+    /// Space, astronomy, astrophysics
+    Space,
+    /// Finance, trading, risk modeling
+    Finance,
+
+    // ── Meta ──
+    /// Knowledge about knowledge — epistemology, meta-learning
+    MetaCognition,
+    /// Benchmark results, comparative analyses
+    Benchmark,
+
     Custom(String),
 }
 
@@ -47,6 +113,30 @@ impl std::fmt::Display for BrainCategory {
             Self::Performance => write!(f, "performance"),
             Self::Tooling => write!(f, "tooling"),
             Self::Debug => write!(f, "debug"),
+            Self::Sota => write!(f, "sota"),
+            Self::Discovery => write!(f, "discovery"),
+            Self::Hypothesis => write!(f, "hypothesis"),
+            Self::CrossDomain => write!(f, "cross_domain"),
+            Self::NeuralArchitecture => write!(f, "neural_architecture"),
+            Self::Compression => write!(f, "compression"),
+            Self::SelfLearning => write!(f, "self_learning"),
+            Self::ReinforcementLearning => write!(f, "reinforcement_learning"),
+            Self::GraphIntelligence => write!(f, "graph_intelligence"),
+            Self::DistributedSystems => write!(f, "distributed_systems"),
+            Self::EdgeComputing => write!(f, "edge_computing"),
+            Self::HardwareAcceleration => write!(f, "hardware_acceleration"),
+            Self::Quantum => write!(f, "quantum"),
+            Self::Neuromorphic => write!(f, "neuromorphic"),
+            Self::BioComputing => write!(f, "bio_computing"),
+            Self::CognitiveScience => write!(f, "cognitive_science"),
+            Self::FormalMethods => write!(f, "formal_methods"),
+            Self::Geopolitics => write!(f, "geopolitics"),
+            Self::Climate => write!(f, "climate"),
+            Self::Biomedical => write!(f, "biomedical"),
+            Self::Space => write!(f, "space"),
+            Self::Finance => write!(f, "finance"),
+            Self::MetaCognition => write!(f, "meta_cognition"),
+            Self::Benchmark => write!(f, "benchmark"),
             Self::Custom(s) => write!(f, "{s}"),
         }
     }

docs/adr/ADR-127-gist-deep-research-loop.md

@@ -0,0 +1,92 @@
+# ADR-127: Gist Deep Research Loop — Brain-Guided Discovery Publishing
+
+**Status:** Implemented
+**Date:** 2026-03-25
+**PR:** #300
+
+## Context
+
+The π Brain's autonomous gist publisher was generating repetitive, low-quality content:
+- Every gist was "X shows weak co-occurrence with Y (confidence: 50%)"
+- Same 8 generic categories recycled (debug, architecture, geopolitics, pattern, solution, tooling, convention, discovery)
+- 45 identical-structure gists published in 48 hours
+- Gemini inflated weak signals into long articles with no substance
+
+Root causes:
+1. Cross-domain similarity threshold too low (0.3 = nearly every pair matches)
+2. Novelty gates trivially easy to pass (2 inferences, 100 evidence)
+3. No quality filter on inference content
+4. No content-based dedup (only title dedup)
+5. Single-pass Gemini rewrite with no external validation
+
+## Decision
+
+### 1. Strict Novelty Gates
+
+Raise all thresholds to require genuinely novel, high-confidence findings:
+
+| Gate | Before | After |
+|------|--------|-------|
+| MIN_NEW_INFERENCES | 2 | 5 |
+| MIN_EVIDENCE | 100 | 500 |
+| MIN_STRANGE_LOOP_SCORE | 0.008 | 0.05 |
+| MIN_PROPOSITIONS | 5 | 10 |
+| MIN_PARETO_GROWTH | 1 | 2 |
+| MIN_INFERENCE_CONFIDENCE | — | 0.60 |
+| Rate limit | 4 hours | 24 hours |
+
+### 2. Quality Filters
+
+Add `strong_inferences()` and `strong_propositions()` that reject:
+- "Weak co-occurrence" language
+- Generic cluster IDs as subjects
+- Confidence < 60%
+- `co_occurs_with` at confidence < 55%
+
+### 3. Source Signal Quality (symbolic.rs)
+
+Raise thresholds at the proposition extraction level:
+- Cross-domain similarity: 0.3 → 0.45
+- `may_influence`: 0.7 → 0.75
+- `associated_with`: 0.5 → 0.55
+
+### 4. Three-Pass Brain-Guided Research Loop
+
+Replace single-pass Gemini rewrite with iterative research:
+
+```
+Pass 1: Gemini + Google Search Grounding
+  → Research domain topics, find real papers/data (2024-2026)
+  → Return structured findings
+
+Pass 2: Brain Memory Search
+  → Query pi.ruv.io/v1/memories/search for each topic
+  → Get internal context the brain has accumulated
+
+Pass 3: Gemini Synthesis
+  → Combine: brain's autonomous findings + grounded research + brain memories
+  → Produce article that neither source could create alone
+```
+
+The brain guides the research by providing the initial discovery signal (which domains to investigate), and the synthesis loop grounds it in real-world evidence.
+
+### 5. Content Dedup
+
+Replace title-only dedup with `category:dominant_inference` key matching. This prevents publishing "geopolitics associated_with architecture" followed by "architecture associated_with geopolitics".
+
+## Consequences
+
+**Positive:**
+- Gists will only publish ~1/day at most, and only when substantive
+- Content grounded in real papers and data via Google Search
+- Brain memories provide unique internal context
+- No more "weak co-occurrence" noise
+
+**Negative:**
+- May publish nothing for days if no novel signals emerge (acceptable)
+- Three Gemini API calls per publish (cost ~$0.01/gist, negligible)
+- Brain memory search adds ~500ms latency (non-blocking, background task)
+
+**Risks:**
+- If Gemini grounding returns irrelevant results, the fallback raw format is still used
+- Brain memory search requires BRAIN_SYSTEM_KEY env var

npm/packages/ruvllm/npm/darwin-x64/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/ruvllm-darwin-x64",
-  "version": "2.0.0",
+  "version": "2.5.3",
   "description": "RuvLLM native bindings for macOS x64 (Intel)",
   "os": [
     "darwin"

npm/packages/ruvllm/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/ruvllm-linux-x64-gnu",
-  "version": "2.0.0",
+  "version": "2.5.3",
   "description": "RuvLLM native bindings for Linux x64 (glibc)",
   "os": [
     "linux"

npm/packages/ruvllm/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/ruvllm-win32-x64-msvc",
-  "version": "2.0.0",
+  "version": "2.5.3",
   "description": "RuvLLM native bindings for Windows x64 (MSVC)",
   "os": [
     "win32"

npm/packages/ruvllm/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/ruvllm",
-  "version": "2.5.2",
+  "version": "2.5.3",
   "description": "Self-learning LLM orchestration with SONA adaptive learning, HNSW memory, FastGRNN routing, and SIMD inference",
   "main": "dist/cjs/index.js",
   "module": "dist/esm/index.js",

npm/packages/sona/npm/darwin-x64/package.json

@@ -1,10 +1,19 @@
 {
   "name": "@ruvector/sona-darwin-x64",
   "version": "0.1.5",
-  "os": ["darwin"],
-  "cpu": ["x64"],
+  "os": [
+    "darwin"
+  ],
+  "cpu": [
+    "x64"
+  ],
   "main": "sona.darwin-x64.node",
-  "files": ["sona.darwin-x64.node"],
+  "files": [
+    "sona.darwin-x64.node"
+  ],
   "license": "MIT",
-  "repository": {"type": "git", "url": "https://github.com/ruvnet/ruvector.git"}
-}
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/ruvnet/ruvector.git"
+  }
+}

npm/packages/sona/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/sona-linux-x64-gnu",
-  "version": "0.1.3",
+  "version": "0.1.5",
   "os": [
     "linux"
   ],

npm/packages/sona/npm/win32-x64-msvc/package.json

@@ -1,10 +1,19 @@
 {
   "name": "@ruvector/sona-win32-x64-msvc",
   "version": "0.1.5",
-  "os": ["win32"],
-  "cpu": ["x64"],
+  "os": [
+    "win32"
+  ],
+  "cpu": [
+    "x64"
+  ],
   "main": "sona.win32-x64-msvc.node",
-  "files": ["sona.win32-x64-msvc.node"],
+  "files": [
+    "sona.win32-x64-msvc.node"
+  ],
   "license": "MIT",
-  "repository": {"type": "git", "url": "https://github.com/ruvnet/ruvector.git"}
-}
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/ruvnet/ruvector.git"
+  }
+}

npm/packages/sona/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ruvector/sona",
-  "version": "0.1.4",
+  "version": "0.1.5",
   "description": "Self-Optimizing Neural Architecture (SONA) - Runtime-adaptive learning with LoRA, EWC++, and ReasoningBank for LLM routers and AI systems. Sub-millisecond learning overhead, WASM and Node.js support.",
   "main": "index.js",
   "types": "index.d.ts",
@@ -79,4 +79,4 @@
     "@ruvector/sona-win32-x64-msvc": "0.1.4",
     "@ruvector/sona-win32-arm64-msvc": "0.1.4"
   }
-}
+}