New CLI Commands:
- batch-learn: Process multiple learning experiences at once
- subscribe: Stream real-time learning updates (polling)
- watch: Auto-learn from file changes in real-time
New MCP Tools (49 total):
- hooks_batch_learn: Batch process experiences array
- hooks_subscribe_snapshot: Get state deltas for subscriptions
- hooks_watch_status: Get current watch/learning status
Features:
- Batch learning processes multiple experiences efficiently
- Subscribe streams events: learn, route, memory, compress
- Watch monitors file changes and auto-learns patterns
- Co-edit detection in watch mode (files edited within 1 min)
Published as v0.1.71
- Add --postgres flag to `ruvector hooks init` command
- Automatically apply PostgreSQL schema using embedded SQL
- Check for RUVECTOR_POSTGRES_URL or DATABASE_URL environment variable
- Provide helpful error messages and manual instructions if psql unavailable
- Update README with new --postgres flag documentation
- Convert serde_json::Value to string for ToSql in remember()
- Parse metadata string back to JSON in recall()
- Pass get_intelligence_path() to Intelligence::new()
- Make get_intelligence_path() public for cross-module access
New hooks added:
- UserPromptSubmit: Inject learned context before processing prompts
- Notification: Track notification patterns
- Task matcher in PreToolUse: Validate agent assignments before spawning
New commands:
- suggest-context: Returns learned patterns for context injection
- track-notification: Records notification events as trajectories
Optimizations:
- Timeout tuning: 1-5s per hook (vs 60s default)
- SessionStart: Separate startup vs resume matchers
- PreCompact: Separate auto vs manual matchers
- Stdin JSON parsing: Full HookInput struct with all Claude Code fields
- Context injection: HookOutput with additionalContext for PostToolUse
Technical improvements:
- HookInput struct: session_id, tool_input, tool_response, notification_type
- HookOutput struct: additionalContext, permissionDecision for control flow
- try_parse_stdin(): Non-blocking JSON parsing from stdin
- output_context_injection(): Helper for PostToolUse context injection
Now covers all 7 Claude Code hook types with optimized timeouts.
Add comprehensive hooks subcommand to ruvector CLI with:
Core Commands:
- init: Initialize hooks in project
- install: Install hooks into Claude settings
- stats: Show intelligence statistics
Hook Operations:
- pre-edit/post-edit: File editing intelligence
- pre-command/post-command: Command execution hooks
- session-start/session-end: Session management
- pre-compact: Pre-compact hook
Memory & Learning:
- remember: Store content in semantic memory
- recall: Search memory semantically
- learn: Record Q-learning trajectories
- suggest: Get best action for state
- route: Route task to best agent
V3 Intelligence:
- record-error: Learn from error patterns
- suggest-fix: Get fixes for error codes
- suggest-next: Predict next files to edit
- should-test: Check if tests should run
Swarm/Hive-Mind:
- swarm-register: Register agents
- swarm-coordinate: Record coordination
- swarm-optimize: Optimize task distribution
- swarm-recommend: Get best agent
- swarm-heal: Handle agent failures
- swarm-stats: Show swarm statistics
All commands tested and working. Data persists to
~/.ruvector/intelligence.json for cross-session learning.
- Format all Rust code with cargo fmt
- Generate Cargo.lock for security audit
- Add build:wasm script to graph-wasm package.json
- Update npm/package-lock.json
The CI was failing due to:
1. Rust code formatting check failures
2. Missing Cargo.lock file for cargo audit
3. Missing build:wasm script expected by graph-ci.yml workflow
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major new package implementing a distributed hypergraph database with:
## Core Components (crates/ruvector-graph/)
- Cypher-compatible query parser with lexer, AST, optimizer
- Query execution engine with SIMD optimization and parallel execution
- ACID transaction support with MVCC isolation levels
- Distributed consensus and federation layer
- Vector-graph hybrid queries for AI/RAG workloads
- Performance optimizations (100x faster than Neo4j target)
## Bindings
- WASM bindings (crates/ruvector-graph-wasm/)
- NAPI-RS Node.js bindings (crates/ruvector-graph-node/)
- NPM packages for both targets
## CLI Integration
- 8 new graph commands: create, query, shell, import, export, info, benchmark, serve
## CI/CD
- Updated build-native.yml for graph packages
- New graph-ci.yml for testing and benchmarks
- New graph-release.yml for automated publishing
## Data Generation
- OpenRouter/Kimi K2 integration (packages/graph-data-generator/)
- Agentic-synth benchmark suite integration
## Tests & Benchmarks
- 11 test files covering all components
- Criterion benchmarks for performance validation
- Neo4j compatibility test suite
## Architecture Highlights
- CSR graph layout for cache-friendly access
- SIMD-vectorized query operators
- Roaring bitmaps for label indexes
- Bloom filters for fast negative lookups
- Adaptive radix tree for property indexes
Note: This is a comprehensive implementation created by 15 parallel agents.
Some integration fixes may be needed to resolve cross-module dependencies.
Co-authored-by: Claude AI Swarm <swarm@claude.ai>
