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The WP33 audit (#919) returned one strong result and four corrections. Two of the corrections were claims that would otherwise have travelled downstream as facts, so they are recorded before the ADRs merge. The enforcement guarantee held under brute force and is now evidenced rather than asserted: 24,300 constructible configurations times 5 mandatory operations is 121,500 checks, zero bypasses. The forced purchase, classification-before-detection ordering, union-not-first-match classification, must_use outcome, the cost>0 and round-cap pair, the oracle exit with its non-finite guard, and unit-range rescaling all verified clean. Four corrections, each of which narrows a claim rather than weakening the mechanism: The 0.06% overhead figure now never appears without its caveat. It is honest for what it measures -- the ladder's own cost with an instant-return fixture, and the accounting genuinely wraps classification, detection, the VoI decision, investigation and observation -- but it is not the number the <5% target is about. With investigators that sleep their declared latency the measured overhead is 14.8%, roughly three times target. Both numbers and what each measures are stated. The <5% target is unenforced, and said so plainly. latency_price defaults to 0.0, so a rung declaring ten seconds costs what a 0us rung costs, and only max_rounds bounds wall-clock cost. Pricing latency honestly refuses the shipped reference ladder at construction, so the honest configuration is currently hard to reach. "100% inspection of mandatory classes" is not yet a checkable metric. mandatory_inspections has no denominator, so a run of 200 operations each matching all five mandatory classes reported zero -- correct behaviour, since they halted fail-closed before purchase, but indistinguishable from a ladder that silently stopped classifying. Enforcement is airtight; the measurement of it is not, and the ADR now separates the two. The module is not wired into the gate's request path, so nothing in the ADR describes the running system. Deployment status is explicit, and #921 (42 crates including bundled SQLite, ndarray and safetensors pulled into a security gate's closure to reuse six pure-math items) should land first. Also recorded: the recognition gap does not close by swapping the detector. Recognition lives in the classes.rs marker list, not in KeywordDetector, so a better detector changes nothing. ADR-335 gains the #920 field evidence, which strengthens its own argument: the flywheel's hard_regression gate is permanently stuck closed, rejecting 120 of 120 candidates across 30 unattended generations including 30 that were strictly better on primary, recall, qps and cost, because it tests an absolute threshold rather than comparing to baseline. That is the case for per-repo declaration made empirically rather than rhetorically. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_016QSCkKnxDjqU49NVVpWMK5 |
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RuVector Documentation
Complete documentation for RuVector, the high-performance Rust vector database with global scale capabilities.
📚 Documentation Structure
docs/
├── adr/ # Architecture Decision Records
├── analysis/ # Research & analysis docs
├── api/ # API references (Rust, Node.js, Cypher)
├── architecture/ # System design docs
├── benchmarks/ # Performance benchmarks & results
├── cloud-architecture/ # Cloud deployment guides
├── code-reviews/ # Code review documentation
├── dag/ # DAG implementation
├── development/ # Developer guides
├── examples/ # SQL examples
├── gnn/ # GNN/Graph implementation
├── guides/ # User guides & tutorials
├── hnsw/ # HNSW index documentation
├── hooks/ # Hooks system documentation
├── implementation/ # Implementation details & summaries
├── integration/ # Integration guides
├── nervous-system/ # Nervous system architecture
├── optimization/ # Performance optimization guides
├── plans/ # Implementation plans
├── postgres/ # PostgreSQL extension docs
├── project-phases/ # Development phases
├── publishing/ # NPM publishing guides
├── research/ # Research documentation
├── ruvllm/ # RuVLLM documentation
├── security/ # Security audits & reports
├── sparse-inference/ # Sparse inference docs
├── sql/ # SQL examples
├── testing/ # Testing documentation
└── training/ # Training & LoRA docs
Getting Started
- guides/GETTING_STARTED.md - Getting started guide
- guides/BASIC_TUTORIAL.md - Basic tutorial
- guides/INSTALLATION.md - Installation instructions
- guides/AGENTICDB_QUICKSTART.md - AgenticDB quick start
- guides/wasm-api.md - WebAssembly API documentation
Architecture & Design
- architecture/ - System architecture details
- cloud-architecture/ - Global cloud deployment
- adr/ - Architecture Decision Records
- nervous-system/ - Nervous system architecture
API Reference
- api/RUST_API.md - Rust API reference
- api/NODEJS_API.md - Node.js API reference
- api/CYPHER_REFERENCE.md - Cypher query reference
Performance & Benchmarks
- benchmarks/ - Performance benchmarks & results
- optimization/ - Performance optimization guides
- analysis/ - Research & analysis docs
Security
- security/ - Security audits & reports
Implementation
- implementation/ - Implementation details & summaries
- integration/ - Integration guides
- code-reviews/ - Code review documentation
Specialized Topics
- gnn/ - GNN/Graph implementation
- hnsw/ - HNSW index documentation
- postgres/ - PostgreSQL extension docs
- ruvllm/ - RuVLLM documentation
- training/ - Training & LoRA docs
Development
- development/CONTRIBUTING.md - Contribution guidelines
- development/MIGRATION.md - Migration guide
- testing/ - Testing documentation
- publishing/ - NPM publishing guides
Research
- research/ - Research documentation
- cognitive-frontier/ - Cognitive frontier research
- gnn-v2/ - GNN v2 research
- latent-space/ - HNSW & attention research
- mincut/ - MinCut algorithm research
🚀 Quick Links
For New Users
- Start with Getting Started Guide
- Try the Basic Tutorial
- Review API Documentation
For Cloud Deployment
- Read Architecture Overview
- Follow Deployment Guide
- Apply Performance Optimizations
For Contributors
- Read Contributing Guidelines
- Review Architecture Decisions
- Check Migration Guide
For Performance Tuning
- Review Optimization Guide
- Run Benchmarks
- Check Analysis
📊 Documentation Status
| Category | Directory | Status |
|---|---|---|
| Getting Started | guides/ | ✅ Complete |
| Architecture | architecture/, adr/ | ✅ Complete |
| API Reference | api/ | ✅ Complete |
| Performance | benchmarks/, optimization/, analysis/ | ✅ Complete |
| Security | security/ | ✅ Complete |
| Implementation | implementation/, integration/ | ✅ Complete |
| Development | development/, testing/ | ✅ Complete |
| Research | research/ | 📚 Ongoing |
Total Documentation: 460+ documents across 60+ directories
🔗 External Resources
- GitHub Repository: https://github.com/ruvnet/ruvector
- Main README: ../README.md
- Changelog: ../CHANGELOG.md
- License: ../LICENSE
Last Updated: 2026-02-26 | Version: 2.0.4 (core) / 0.1.100 (npm) | Status: Production Ready